CN115657598B - Machine tool simulation optimization design method and system based on fuzzy evaluation - Google Patents
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Abstract
The invention provides a machine tool simulation optimization design method and system based on fuzzy evaluation, which construct a simulation optimization model of alternative machine tool performance through mutual coupling of a simulation means and a test means, execute operation monitoring to obtain a real cutting performance index of a machine tool under a cutting condition of the machine tool and correct the model, execute simulation analysis of the machine tool after the cutting condition is split to obtain an optimized structure index, obtain an optimized structure index with the highest evaluation value, execute operation monitoring under the preferred cutting condition to obtain a preferred real cutting performance index of the machine tool, compare the preferred real cutting performance index with the optimized structure index with the highest evaluation value, verify and output a structure index design optimization result of the machine tool. On the basis of comprehensively considering the material selection, the structural design and the optimization, the invention integrates the engineering experience of researchers, combines the subjective qualitative analysis and the objective data quantitative calculation, and can avoid the one-sidedness caused by single qualitative analysis or quantitative analysis.
Description
Technical Field
The invention relates to the technical field of reliability evaluation of numerical control equipment structure design, in particular to a machine tool simulation optimization design method and system based on fuzzy evaluation.
Background
The reliability of the structure design of the numerical control machine tool refers to the performance of the structure design process determined to maintain the quality of machining and to achieve the purpose of the machine tool within a required specified period and at a specified productivity. That is, not only the initial high precision of the nc machine but also the accuracy, efficiency and cost thereof are maintained for a prescribed life, and the reliability of the structural design of the nc machine is concerned with the maintenance of the function and technical performance of the nc machine during the machining process. The technology for evaluating the reliability of the structural design of the numerical control machine is one of necessary means for quantitatively controlling the structural design reliability of the numerical control machine, and mainly aims to measure whether the numerical control machine achieves an expected design target and use requirements, indicate weak links in the machining process of the numerical control machine and indicate directions for improving the design, manufacture, structural design, maintenance and the like of the numerical control machine.
Due to the structure and complex operating environment of a large numerical control machine, the occurrence of machine failure is generally difficult to predict, and the influence of failure among functional components, the failure probability characteristic of a feature, the failure growth of a feature, the changing operating environment and the changing structural design parameters all increase the complexity of reliability data. Meanwhile, compared with medium and small numerical control machines, the large numerical control machine is not only complicated and huge with the processed workpiece, but also has large processing load change and large processing stroke. With the increasing requirements of users on machining precision, machining efficiency and reliability, machining parameters such as machining precision, feed speed, acceleration and reliability are also continuously improved, so that factors in the aspect of dynamic characteristics, which have little influence on machining precision under the traditional machining condition, are caused, and the machining precision is obviously influenced under the machining conditions of high speed, high acceleration and large variable load.
By comprehensively observing the current research progress and results at home and abroad, the following obvious problems and technical difficulties to be solved urgently still exist in the field of the optimization design of the dynamic performance of the complete machine of the numerical control machine tool: at present, a test piece with specific geometric characteristics is directly processed on a numerical control machine tool, the motion control performance of the numerical control device is judged by using the final geometric size of the processed test piece, but the final geometric size and the processing precision of the test piece are influenced by multiple factors, besides the factors of the numerical control device, the position error of a servo feeding system of the machine tool, the geometric precision of the machine tool, the measurement error of the test piece and the like, and the motion control performance of the numerical control device cannot be accurately evaluated by a method for processing the test piece on the machine tool. When the finite element analysis result of the whole machine is compared with the test result, the correctness of the modeling of the whole machine is usually judged only according to whether the natural frequency of the machine tool is consistent, so that the correctness of the established dynamic model of the whole machine is not enough to be determined.
The fuzzy evaluation method, the grey correlation method and other methods which are proposed by scholars at present can solve the problem that multiple schemes and multiple evaluation indexes are difficult to accept in the optimization design of the machine tool structural part, and the subjectivity of designers is avoided when weights are calculated, but the defects are that the structural hierarchy of the evaluation process is not clear enough, and an evaluation method of a scientific system is not proposed when multiple evaluation indexes such as quality, deformation, inherent frequency and stress of multiple design schemes of the machine tool structural part are comprehensively considered, and the problem can be solved by the fuzzy evaluation simulation optimization design scheme of the machine tool structural part constructed in the method.
Disclosure of Invention
The invention aims to provide a machine tool simulation optimization design method and system based on fuzzy evaluation aiming at the defects of the prior art, comprehensively considers the influence of various factors on the functions and the performances of a large numerical control machine tool in the machining process of the machine tool, and improves the accuracy of the reliability of structural design.
In a first aspect, the invention provides a machine tool simulation optimization design method based on fuzzy evaluation, which is characterized by comprising the following steps:
constructing a performance simulation optimization model of the alternative machine tool, and obtaining an alternative structure index through the performance simulation optimization model of the alternative machine tool;
monitoring the operation of the machine tool to obtain a plurality of real cutting performance indexes of the machine tool under a plurality of cutting conditions of the machine tool;
correcting the alternative machine tool performance simulation optimization model according to the real cutting machining performance indexes to obtain a corrected machine tool simulation model;
splitting the plurality of machine tool cutting conditions to obtain a plurality of atomic cutting conditions, and performing machine tool simulation analysis on the plurality of atomic cutting conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes;
constructing a machine tool performance simulation fuzzy evaluation method, and respectively inputting a plurality of optimized structure indexes into the machine tool performance simulation fuzzy evaluation method to obtain the optimized structure index with the highest evaluation value, wherein the atomic cutting processing condition corresponding to the optimized structure index with the highest evaluation value is used as a preferred cutting processing condition;
according to the first-choice cutting machining condition, performing operation monitoring to obtain a first-choice real cutting machining performance index of the machine tool, and performing comparison between the first-choice real cutting machining performance index and an optimized structure index with the highest evaluation value to obtain a structure index design optimization result of the machine tool;
the alternative machine tool performance simulation optimization model comprises a static performance simulation optimization model, a dynamic performance simulation optimization model and a thermal deformation performance simulation optimization model, and the alternative structure index is obtained based on the static performance simulation optimization model, the dynamic performance simulation optimization model and the thermal deformation performance simulation optimization model;
the static performance simulation optimization model is characterized as follows:
in the expression (2), i represents a turntable,
the lead of the lead screw is shown,
the radial bearing bore area is shown as,
which is indicative of the density of the material,
the diameter of the guide rail is shown,
denotes the coefficient of elasticity of the material, t denotes the number of oil pads,
which represents the load of the ring gear,
represents the cutting force; expression (2) is applicable to heavy machine tools;
the dynamic performance simulation optimization model is characterized as follows:
in expressions (3) and (4)
Shows the density of main structural parts (ram, ram seat, column, slide seat and bed), RV shows the elasticity modulus of the veneering at the main junction surface (bed slide seat junction surface, column ram seat junction surface and ram seat ram junction surface),
the static and dynamic stiffness of the whole machine is shown,
the maximum deformation of the whole machine is shown, t is the number of oil pads,
which represents the maximum deformation of the end of the spindle,
representing the natural frequency of the front stage of the whole machine;
the lead of the lead screw is shown,
the rigidity of the nut pair is shown,
the radial bearing bore area is shown as,
the position loop gain is shown as a function of,
the gain of the speed loop is shown,
the average milling force is shown as a function of,
represents the feed speed;
the thermal deformation performance simulation optimization model is characterized as follows:
in expression (5)
Indicating the cooling rate, T the reference temperature, T the number of oil pads,
the maximum temperature is indicated and is,
the cut-off temperature is indicated.
Further, the operation monitoring of the machine tool is performed to obtain a plurality of real cutting performance indexes of the machine tool under a plurality of cutting conditions of the machine tool, and the method specifically comprises the following steps:
setting a first machine tool cutting condition and a second machine tool cutting condition of a machine tool;
performing operation monitoring on the machine tool according to the first machine tool cutting condition and the second machine tool cutting condition respectively to obtain a first real cutting performance index and a second real cutting performance index;
correcting the alternative machine tool performance simulation optimization model according to a plurality of real cutting machining performance indexes to obtain a corrected machine tool simulation model, which specifically comprises the following steps:
setting part of alternative structure indexes needing to be corrected in the alternative machine tool performance simulation optimization model based on the first machine tool cutting condition;
obtaining a first simulation structure index performance after the machine tool cutting machining condition is processed by an alternative machine tool performance simulation optimization model;
comparing the first index of the real cutting processing performance with the performance of the simulation structure indexFirstly, when the relative error between the simulation structure index performance I and the real cutting processing performance index I
When the ratio exceeds 20%, correcting part of the alternative structural indexes to obtain fuzzy correction structural indexes;
based on the second cutting machining condition of the machine tool, adjusting the fuzzy correction structure index to obtain a secondary correction structure index;
the second machine tool cutting machining condition is processed by the alternative machine tool performance simulation optimization model to obtain a second simulation structure index performance;
comparing the second real cutting performance index with the second simulated structure index, and determining the relative error between the second simulated structure index and the second real cutting performance index
When the quantity exceeds 20 percent, setting parameters needing to be corrected in the alternative machine tool performance simulation optimization model as secondary correction structural indexes, and correcting the secondary correction structural indexes again based on the machine tool cutting machining conditions until the secondary correction structural indexes are corrected again until the quantity exceeds 20 percent
Not more than 20% and
and if not more than 20%, finishing correction to obtain a corrected machine tool simulation model.
Further, splitting a plurality of machine tool cutting conditions to obtain a plurality of atomic cutting conditions, performing machine tool simulation analysis on the plurality of atomic cutting conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes, specifically comprising:
setting a reasonable value range of machine tool cutting conditions according to a reasonable value range of static deformation [ SSHAPEmin, SSHAPEmax ], a reasonable value range of dynamic deformation [ DSHAPEmin, DSHAPEmax ], a reasonable value range of maximum stress [ Forcemin, forcemax ], a reasonable value range of compound motion deviation [ MoveDemin, moveDemax ];
based on the reasonable value range of the machine tool cutting machining conditions, selecting a static deformation value, b dynamic deformation value, c maximum stress value and d composite motion deviation value in an evenly distributed mode to obtain P atomic cutting machining conditions, wherein a, b, c and d are positive integers;
and respectively executing machine tool simulation analysis under P atomic cutting machining conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes.
Further, a machine tool performance simulation fuzzy evaluation method is constructed, the P optimized structure indexes are respectively input into the machine tool performance simulation fuzzy evaluation method, the optimized structure index with the highest evaluation value is obtained, and the atomic cutting processing condition corresponding to the optimized structure index with the highest evaluation value serves as a preferred cutting processing condition, and the method specifically comprises the following steps:
constructing a machine tool performance simulation fuzzy evaluation method, and obtaining P optimized structure index evaluation values based on P optimized structure indexes;
setting the optimized structure index corresponding to the highest evaluation value in the P optimized structure index evaluation values as the optimized structure index with the highest evaluation value, taking the atomic cutting condition corresponding to the optimized structure index with the highest evaluation value as the preferred cutting condition,
wherein the static deformation level value of the first-choice cutting machining condition is Mx1, the dynamic deformation level value is DSHAPEx2, the maximum stress is Tx3, and the compound motion deviation is Px4;
fuzzy evaluation method for machine tool performance simulationFuzzyNetThe expression is as follows:
wherein,
and represents the degree of membership,
，
，
respectively representing low deformation, medium deformation and high deformation, the numerical values of which are determined according to the P optimized structure indexes,m，n，prespectively representing fuzzy evaluation weight factors, the values of which are reasonable value ranges [0,1 ]]Positive real numbers of (d);
the preferred cutting conditions satisfy the following conditions:
according to a second aspect, the invention claims a machine tool simulation optimization design system based on fuzzy evaluation, which is characterized by comprising:
the alternative simulation optimization model building module: constructing a performance simulation optimization model of the alternative machine tool, and obtaining an alternative structure index through the performance simulation optimization model of the alternative machine tool;
an operation monitoring module: the method comprises the steps of monitoring the operation of a machine tool to obtain a plurality of real cutting performance indexes of the machine tool under a plurality of cutting conditions of the machine tool;
a correction module: correcting the machine tool simulation model according to the real cutting performance indexes to obtain a corrected machine tool simulation model;
a simulation splitting module: splitting the plurality of machine tool cutting conditions to obtain a plurality of atomic cutting conditions, and performing machine tool simulation analysis on the plurality of atomic cutting conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes;
a first-choice evaluation module: establishing a machine tool performance simulation fuzzy evaluation method, and respectively inputting the P optimized structure indexes into the machine tool performance simulation fuzzy evaluation method to obtain an optimized structure index with the highest evaluation value, wherein the atomic cutting machining condition corresponding to the optimized structure index with the highest evaluation value is used as a preferred cutting machining condition;
an optimization and verification module: according to the first-choice cutting machining condition, performing operation monitoring to obtain a first-choice real cutting machining performance index of the machine tool, and performing comparison between the first-choice real cutting machining performance index and an optimized structure index with the highest evaluation value to obtain a structure index design optimization result of the machine tool;
the alternative machine tool performance simulation optimization model comprises a static performance simulation optimization model, a dynamic performance simulation optimization model and a thermal deformation performance simulation optimization model, and the alternative structure index is obtained based on the static performance simulation optimization model, the dynamic performance simulation optimization model and the thermal deformation performance simulation optimization model;
the static performance simulation optimization model is characterized as follows:
in the expression (2), i represents a turntable,
the lead of the lead screw is shown,
the radial bearing bore area is shown as,
which is indicative of the density of the material,
the diameter of the guide rail is shown,
representing the coefficient of elasticity of the material, t representing the number of oil pads,
which represents the load of the ring gear,
represents the cutting force; the expression (2) is suitable for a heavy machine tool;
the dynamic performance simulation optimization model is characterized as follows:
in expressions (3) and (4)
The density of main structural members (ram, ram seat, column, slide seat, bed) is represented, RV represents the veneering elastic modulus at main junction surfaces (bed slide seat junction surface, column ram seat junction surface, ram seat ram junction surface),
the static and dynamic stiffness of the whole machine is shown,
the maximum deformation of the whole machine is shown, t is the number of oil pads,
which represents the maximum deformation of the end of the spindle,
representing the natural frequency of the front stage of the whole machine;
the lead of the lead screw is shown,
the stiffness of the nut pair is shown,
the radial bearing bore area is shown as,
the position loop gain is shown as a function of,
the gain of the speed loop is shown as,
the average milling force is expressed in terms of,
represents the feed rate;
the thermal deformation performance simulation optimization model is characterized as follows:
in expression (5)
Indicating the cooling rate, T the reference temperature, T the number of oil pads,
the maximum temperature is indicated and is,
the cut-off temperature is indicated.
Further, the operation monitoring of the machine tool is performed to obtain a plurality of real cutting performance indexes of the machine tool under a plurality of cutting conditions of the machine tool, and the method specifically comprises the following steps:
setting a first machine tool cutting condition and a second machine tool cutting condition of a machine tool;
respectively executing operation monitoring on the machine tool according to the first machine tool cutting condition and the second machine tool cutting condition to obtain a first real cutting performance index and a second real cutting performance index;
correcting the alternative machine tool performance simulation optimization model according to a plurality of real cutting machining performance indexes to obtain a corrected machine tool simulation model, which specifically comprises the following steps:
setting part of alternative structure indexes to be corrected in an alternative machine tool performance simulation optimization model based on the first machine tool cutting condition;
obtaining a first simulation structure index performance after the machine tool cutting machining condition is processed by an alternative machine tool performance simulation optimization model;
comparing the first true cutting performance index with the first simulated structure index, and determining the relative error between the first simulated structure index and the first true cutting performance index
When the rate exceeds 20%, correcting part of the alternative structural indexes to obtain a fuzzy correction structural index;
based on the second cutting condition of the machine tool, adjusting the fuzzy correction structure index to obtain a secondary correction structure index;
the second machine tool cutting machining condition is processed by the alternative machine tool performance simulation optimization model to obtain a second simulation structure index performance;
comparing the second true cutting performance index with the second simulated structure index, and comparing the second simulated structure index with the second true cutting performance index when the relative error exists between the second simulated structure index and the second true cutting performance index
When the rate exceeds 20%, setting the needed correction in the alternative machine tool performance simulation optimization modelIs a secondary correction structure index, and the secondary correction structure index is corrected again based on the cutting conditions of the machine tool until the secondary correction structure index is corrected again
Not more than 20% and
and (5) finishing correction to obtain a corrected machine tool simulation model, wherein the correction does not exceed 20%.
Further, splitting a plurality of machine tool cutting conditions to obtain a plurality of atomic cutting conditions, performing machine tool simulation analysis on the plurality of atomic cutting conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes, specifically comprising:
setting a reasonable value range of machine tool cutting conditions according to a reasonable value range of static deformation [ SSHAPEmin, SSHAPEmax ], a reasonable value range of dynamic deformation [ DSHAPEmin, DSHAPEmax ], a reasonable value range of maximum stress [ Forcemin, forcemax ], a reasonable value range of compound motion deviation [ MoveDemin, moveDemax ];
based on the reasonable value range of the machine tool cutting machining conditions, selecting SSHAPE static deformation values, dy dynamic deformation values, fmax maximum stress values and MoveDe composite motion deviation values in an evenly distributed mode to obtain P atom cutting machining conditions, wherein the SSHAPE, the Dy, the Fmax and the MoveDe are positive integers;
and respectively executing machine tool simulation analysis under P atomic cutting machining conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes.
Further, a machine tool performance simulation fuzzy evaluation method is constructed, and the P optimized structure indexes are respectively input into the machine tool performance simulation fuzzy evaluation method, so that the optimized structure index with the highest evaluation value is obtained, and the atomic cutting processing condition corresponding to the optimized structure index with the highest evaluation value serves as a preferred cutting processing condition, and the method specifically comprises the following steps of:
constructing a machine tool performance simulation fuzzy evaluation method, and obtaining P optimized structure index evaluation values based on P optimized structure indexes;
setting the optimized structure index corresponding to the highest evaluation value in the P optimized structure index evaluation values as the optimized structure index with the highest evaluation value, taking the atomic cutting condition corresponding to the optimized structure index with the highest evaluation value as the preferred cutting condition,
wherein the static deformation level value of the first-choice cutting machining condition is Mx1, the dynamic deformation level value is DSHAPEx2, the maximum stress is Tx3, and the compound motion deviation is Px4;
fuzzy evaluation method for machine tool performance simulationFuzzyNetThe expression is as follows:
wherein,
the degree of membership is represented by,
，
，
respectively representing low deformation, medium deformation and high deformation, the numerical values of which are determined according to the P optimized structure indexes,m，n，prespectively representing fuzzy evaluation weight factors, the values of which are reasonable value ranges [0,1 ]]Positive real numbers of (d);
the preferred cutting conditions satisfy the following conditions:
the invention provides a machine tool simulation optimization design method and system based on fuzzy evaluation, which construct a simulation optimization model of alternative machine tool performance through mutual coupling of a simulation means and a test means, execute operation monitoring to obtain a real cutting performance index of a machine tool under a cutting condition of the machine tool and correct the model, execute simulation analysis of the machine tool after the cutting condition is split to obtain an optimized structure index, obtain the optimized structure index with the highest evaluation value based on the fuzzy evaluation method, execute operation monitoring under the first-choice cutting condition to obtain the first-choice real cutting performance index of the machine tool, compare the first-choice real cutting performance index with the optimized structure index with the highest evaluation value, verify and output the structure index design optimization result of the machine tool. On the basis of comprehensively considering the material selection, the structural design and the optimization, the method can integrate the engineering experience of researchers, combine subjective qualitative analysis and objective data quantitative calculation, and avoid one-sidedness caused by single qualitative analysis or quantitative analysis.
Drawings
Fig. 1 is an overall flow diagram of a machine tool simulation optimization design method based on fuzzy evaluation according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a verification and correction process between a simulation model and a real machining performance index of a machine tool simulation optimization design method based on fuzzy evaluation according to an embodiment of the present application;
fig. 3 is a block diagram of a structure of a machine tool simulation optimization design system based on fuzzy evaluation according to an embodiment of the present application.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. It will be understood that the terms "first," "second," and the like, as used herein, may be used herein to describe various elements, but these elements are not limited by these terms unless otherwise specified. These terms are only used to distinguish one element from another. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
Fig. 1 is a schematic overall flow chart of a machine tool simulation optimization design method based on fuzzy evaluation according to an embodiment of the present application. The following description of the specific steps of the inventive method is provided by way of specific computing embodiments in conjunction with the accompanying drawings.
According to a first embodiment, the invention provides a machine tool simulation optimization design method based on fuzzy evaluation, which is characterized by comprising the following steps:
step (1), constructing an alternative machine tool performance simulation optimization model, and obtaining an alternative structure index through the alternative machine tool performance simulation optimization model;
step (2), monitoring the operation of the machine tool to obtain a plurality of real cutting performance indexes of the machine tool under the cutting conditions of the machine tool;
step (3), correcting the alternative machine tool performance simulation optimization model according to the real cutting machining performance indexes to obtain a corrected machine tool simulation model;
step (4), splitting the plurality of machine tool cutting conditions to obtain a plurality of atomic cutting conditions, and performing machine tool simulation analysis on the plurality of atomic cutting conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes;
step (5), a machine tool performance simulation fuzzy evaluation method is constructed, and the optimized structure indexes are respectively input into the machine tool performance simulation fuzzy evaluation method, so that the optimized structure index with the highest evaluation value is obtained, and the atomic cutting machining condition corresponding to the optimized structure index with the highest evaluation value is used as a preferred cutting machining condition;
step (6), according to the preferred cutting machining condition, running monitoring is executed, a preferred real cutting machining performance index of the machine tool is obtained, the preferred real cutting machining performance index is compared with an optimized structure index with the highest evaluation value, and a structure index design optimization result of the machine tool is obtained;
the alternative machine tool performance simulation optimization model comprises a static performance simulation optimization model, a dynamic performance simulation optimization model and a thermal deformation performance simulation optimization model, and the alternative structural index is obtained based on the static performance simulation optimization model, the dynamic performance simulation optimization model and the thermal deformation performance simulation optimization model;
the static performance simulation optimization model is characterized as follows:
in the expression (2), i represents a turntable,
the lead of the lead screw is shown,
the radial bearing bore area is shown as,
which is indicative of the density of the material,
the diameter of the guide rail is shown,
denotes the coefficient of elasticity of the material, t denotes the number of oil pads,
which represents the load of the ring gear,
represents the cutting force; the expression (2) is suitable for a heavy machine tool;
the dynamic performance simulation optimization model is characterized as follows:
in expressions (3) and (4)
The density of main structural members (ram, ram seat, column, slide seat, bed) is represented, RV represents the veneering elastic modulus at main junction surfaces (bed slide seat junction surface, column ram seat junction surface, ram seat ram junction surface),
the static and dynamic stiffness of the whole machine is shown,
the maximum deformation of the whole machine is shown, t is the number of oil pads,
which represents the maximum deformation of the end of the spindle,
representing the natural frequency of the front stage of the whole machine;
the lead of the lead screw is shown,
the stiffness of the nut pair is shown,
the radial bearing bore area is shown as,
the position loop gain is shown as a function of,
the gain of the speed loop is shown,
the average milling force is shown as a function of,
represents the feed speed;
the thermal deformation performance simulation optimization model is characterized as follows:
in expression (5)
Indicating the cooling rate, T the reference temperature, T the number of oil pads,
the maximum temperature is indicated and is,
the cut-off temperature is indicated.
Further, the operation monitoring of the machine tool is performed to obtain a plurality of real cutting performance indexes of the machine tool under a plurality of cutting conditions of the machine tool, and the method specifically comprises the following steps:
setting a first machine tool cutting condition and a second machine tool cutting condition of a machine tool;
performing operation monitoring on the machine tool according to the first machine tool cutting condition and the second machine tool cutting condition respectively to obtain a first real cutting performance index and a second real cutting performance index;
correcting the alternative machine tool performance simulation optimization model according to a plurality of real cutting machining performance indexes to obtain a corrected machine tool simulation model, which specifically comprises the following steps:
setting part of alternative structure indexes to be corrected in an alternative machine tool performance simulation optimization model based on the first machine tool cutting condition;
obtaining a first simulation structure index performance after the machine tool cutting machining condition is processed by an alternative machine tool performance simulation optimization model;
comparing the first true machinability index with the first simulated structure index, and comparing the relative error between the first simulated structure index and the first true machinability index
When the rate exceeds 20%, correcting part of the alternative structural indexes to obtain a fuzzy correction structural index;
based on the second cutting machining condition of the machine tool, adjusting the fuzzy correction structure index to obtain a secondary correction structure index;
the second machine tool cutting machining condition is processed by the alternative machine tool performance simulation optimization model to obtain a second simulation structure index performance;
comparing the second real cutting performance index with the second simulated structure index, and determining the relative error between the second simulated structure index and the second real cutting performance index
When the rate of change exceeds 20%, setting parameters needing to be corrected in the alternative machine tool performance simulation optimization model as secondary correction structure indexes, and correcting the secondary correction structure indexes again based on machine tool cutting conditions until the secondary correction structure indexes are corrected again until the rate of change is higher than 20%
Not more than 20% and
not more than 20%, completing the correction to obtain the correctionA positive machine tool simulation model.
Further, splitting a plurality of machine tool cutting conditions to obtain a plurality of atomic cutting conditions, performing machine tool simulation analysis on the plurality of atomic cutting conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes, specifically comprising:
setting a reasonable value range of machine tool cutting conditions according to a reasonable value range [ SSHAPEmin, SSHAPEmax ] of the static deformation, a reasonable value range [ DSHAPEmin, DSHAPEmax ] of the dynamic deformation, a reasonable value range [ Forcemin, forcemax ] of the maximum stress, and a reasonable value range [ MoveDemin, moveDemax ] of the compound motion deviation;
based on the reasonable value range of the machine tool cutting machining conditions, selecting a static deformation value, b dynamic deformation value, c maximum stress value and d composite motion deviation value in an evenly distributed mode to obtain P atomic cutting machining conditions, wherein a, b, c and d are positive integers;
and respectively executing machine tool simulation analysis under P atomic cutting machining conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes.
Further, a machine tool performance simulation fuzzy evaluation method is constructed, the P optimized structure indexes are respectively input into the machine tool performance simulation fuzzy evaluation method, the optimized structure index with the highest evaluation value is obtained, and the atomic cutting processing condition corresponding to the optimized structure index with the highest evaluation value serves as a preferred cutting processing condition, and the method specifically comprises the following steps:
constructing a machine tool performance simulation fuzzy evaluation method, and obtaining P optimized structure index evaluation values based on P optimized structure indexes;
setting the optimized structure index corresponding to the highest evaluation value in the P optimized structure index evaluation values as the optimized structure index with the highest evaluation value, taking the atomic cutting condition corresponding to the optimized structure index with the highest evaluation value as the preferred cutting condition,
wherein the static deformation horizontal value of the first-choice cutting machining condition is Mx1, the dynamic deformation horizontal value is DSHAPEx2, the maximum stress is Tx3, and the compound motion deviation is Px4;
fuzzy evaluation method for machine tool performance simulationFuzzyNetThe expression is as follows:
wherein,
the degree of membership is represented by,
，
，
respectively representing low deformation, medium deformation and high deformation, the numerical values of which are determined according to the P optimized structure indexes,m，n，prespectively representing fuzzy evaluation weight factors, the numerical values of which are reasonable value ranges [0, 1%]Positive real number of (d);
the preferred cutting conditions satisfy the following conditions:
according to another embodiment of the present invention, the structure optimization design for the machine tool may further include:
1) Performing digitalized performance index simulation on the machine tool;
2) Integrally planning the manufacture of the real structure according to the performance index of the machine tool;
3) Constructing a fuzzy evaluation model for manufacturing the real structure according to the overall planning of manufacturing the real structure, and integrating and fusing the model to generate a simulation structure;
4) Carrying out simulation verification on the manufacturing of the simulation structure;
5) According to the simulation result, if the design requirement is met, starting step 6), if the overall plan does not meet the design requirement, returning to step 2), and if the constructed fuzzy evaluation model does not meet the design requirement, returning to step 3);
6) Building a real structure according to the verified simulation structure;
7) And establishing a bidirectional mapping relation between the real structure manufacturing and the simulation structure manufacturing, and realizing the control of the simulation structure manufacturing on the real structure manufacturing.
1) In the middle, performing digitalized performance index simulation on the machine tool; the digitalized performance simulation index for the machine tool takes a three-dimensional digital model of the machine tool as a core, an integrated three-dimensional entity model replaces a traditional two-dimensional engineering drawing, and the machine tool explicit geometric dimension information and the recessive structure design information are completely expressed based on structural design guidance information such as three-dimensional PMI marking information, structural design annotation technical diagrams, three-dimensional simulation animations and process description information, so that the holographic expression of a product three-dimensional structure design file is realized. The specific implementation comprises the steps of establishing a structure design structure, designing a structure design route, finishing detailed performance indexes, establishing a three-dimensional model of the machine tool and carrying out three-dimensional labeling.
2) In the method, the manufacture of the real structure is integrally planned according to the performance indexes of the machine tool: the overall planning of structure manufacturing refers to determining the type and quantity of equipment by combining site characteristics, machine tool characteristics and special requirements, determining the cutting content of each procedure, and formulating a production flow and an equipment circulation sequence; planning the whole arrangement of structure manufacture and determining the motion form and the motion path.
3) And constructing a fuzzy evaluation model for manufacturing the real structure according to the overall planning of manufacturing the real structure, and integrating and fusing the model to generate the simulation structure.
The three layers of the component, the operation flow and the strategy are divided into component layer modeling for structure manufacturing, operation flow layer modeling for structure manufacturing and strategy layer modeling for structure manufacturing. The structural manufacturing component is mainly equipment, and the equipment fuzzy evaluation model comprises: three-dimensional model of the equipment, position information of digital space, running process of the equipment and virtual and real interfaces. The specific implementation method comprises the steps of establishing a three-dimensional model of equipment, determining position information of a digital space, establishing an equipment model library, modeling a motion mechanism and a motion attitude of the equipment with motion attributes, and determining an equipment operation process.
The operation flow layer modeling of the structure manufacturing is determined on the basis of a component layer model, driving and disturbance factors are added, and the characteristics of the sequence, concurrency, linkage and the like of the components manufactured by the structure are described. The specific implementation mode is that virtual and real interface input parameters of the equipment fuzzy evaluation model are set, and corresponding control logic is compiled during simulation so as to control the sequential, concurrent and linkage operation flows of the structure manufacturing equipment.
And the strategic layer modeling is used for mapping the strategic rules of the structure manufacturing to the corresponding component model and the operation process model. The specific implementation mode is to establish signal links of all component models and set judgment conditions of the operation flow model control logic.
And integrating and fusing the structure manufacturing fuzzy evaluation model to form simulation structure manufacturing consistent with real-time position, pose, speed and state information of a machine tool, an industrial robot, a workpiece and a material unit in the real world.
4) Carrying out simulation verification on the manufacturing of a simulation structure; the simulation verification of the structure manufacturing mainly carries out simulation trial operation on a machine tool, a robot and a logistics system related in the production process in the part implementation process according to the structural design route of the part, and carries out visualization presentation in a uniform three-dimensional representation form. The embodiment is that a PLC control logic is written and used as a simulation input of the simulation structure manufacture, and the communication between the simulation structure manufacture and the actual PLC is realized by TCP/IP, field bus or Ethernet and the like.
5) And calculating information such as the production rhythm, the equipment utilization rate and the like of the part according to the simulation result, starting 6) if the design requirement is met, returning 2) if the overall planning does not meet the design requirement, and returning 3) if the constructed fuzzy evaluation model does not meet the design requirement.
6) According to the verified simulation structure manufacturing, real structure manufacturing is constructed; the construction of real structure manufacture follows the requirements of structural design layout, the structure manufacture constructed in the real world is communicated with information flow, real logistics and control flow of software and hardware systems such as machine tools, industrial robots, sensors, detection units, warehouse logistics, management and control platforms and the like.
7) In the method, a bidirectional mapping relation between real structure manufacturing and simulation structure manufacturing is established, and the control of the simulation structure manufacturing on the real structure manufacturing is realized. Real data are collected in real time through a PLC, the structure manufacturing management and control system reads the real data and packages the data into a uniform interface form, the real data are input into a simulation model through a uniform data structure, and forward input mapping from the real data to the simulation model is achieved. The simulation process/result data generated by the simulation model is stored in an XML file expressed in a specific format, and feedback information is generated through the data processing and analyzing module, so that negative feedback mapping is established. The simulation model adopts a single-step solving mode and is simulated synchronously with real time; based on a bidirectional mapping technology of a simulation model and real data, each simulation single step can receive a real state and inject the real state into the model in real time, and the real state is used as an input condition for next solving of the model to simulate the running state of a real object in real time.
FIG. 2 is a schematic diagram of a verification and correction process between a simulation model and a real machining performance index of a machine tool simulation optimization design method based on fuzzy evaluation according to an embodiment of the present application;
specifically, the step (2) further comprises:
the machine tool is placed on the machine tool rotary table, and a gas supply pipeline, a punch press load and the like are connected. And after the rigidity detection of the standby machine tool is qualified, performing initial detection on the machine tool according to the initial detection cutting machining conditions specified by the machine tool specification until the initial detection process is finished.
Setting a first machine tool cutting condition of the machine tool based on the test and simulation requirements of the machine tool, wherein the first machine tool cutting condition comprises a static deformation amount of SSHAPE1, a dynamic deformation amount of DSHAPE1, a maximum stress of T1 and a compound motion deviation of P1;
setting a second machine tool cutting condition of the machine tool based on the test and simulation requirements of the machine tool, wherein the static deformation of the second machine tool cutting condition is SSHAPE2, the dynamic deformation is DSHAPE2, the maximum stress is T2, and the compound motion deviation is P2;
and performing operation monitoring on the machine tool according to the first cutting condition of the machine tool and the second cutting condition of the machine tool to obtain a first real cutting performance index and a second real cutting performance index.
In some embodiments, the testing and simulation requirements of the machine tool are generally selected based on an instruction manual of a machine tool sample, that is, personalized customization can be performed according to the requirements of a customer, so long as a working condition combination is selected from any working condition combination (for example, the maximum stress is 60-90%, the dynamic deformation is 40% -100% and the like) within a cutting machining condition range of sample operation, and the universal adaptability is provided for all working conditions.
And setting the test cutting condition of the turntable according to the parameter of the first cutting condition of the machine tool, and testing the machine tool to obtain a relation graph between the structural index design and the deformation, namely the polarization curve performance of the machine tool under the first cutting condition of the machine tool.
And setting the test cutting condition of the turntable according to the parameters of the second cutting condition of the machine tool, and testing the machine tool to obtain a relation graph between the structural index design and the deformation, namely the polarization curve performance of the machine tool under the second cutting condition of the machine tool.
Specifically, the step (3) further comprises: setting corresponding parameters in the simulation model based on the structure and design parameters of the actual measurement machine tool:
in some embodiments, the radial bearing bore area: 200 mm (mm) 2 (ii) a Thickness of the ram: 5500 mm; thickness of the ram seat: 520 mm; the thickness of the upright column: 350 mm; thickness of the sliding seat: 750 mm; bed body thickness: 1.2m.
Ram density: 7.9 g cm -3 (ii) a Column density: 9.5 g cm -3 (ii) a Density of the sliding seat: 10 g cm -3 (ii) a Bed body density: 12.5 g cm -3 (ii) a Density of main structural members (ram, ram seat, column, slide, bed): 8.9 g cm -3 。
Ram stiffness value: 120 N/M; column stiffness value: 200 N/M; the rigidity value of the sliding seat is as follows: 155 N/M; bed body rigidity value: 180 N/M.
Lathe bed lead screw: 10mm; slide lead screw lead: 12mm; column lead screw lead: 20mm.
Based on the parameters of the cutting condition 1 in the real cutting performance indexes, setting part of alternative structure indexes in the simulation model:
the static deformation of the whole bed and the structural part is respectively as follows: 75
，22
。
The composite motion deviation of the whole bed and the structural part is respectively as follows: 18
，1.9
。
The dynamic deformation of the whole bed and the structural part is respectively as follows: 125
，48
。
The maximum stress of the whole bed and the structural part is respectively as follows: 125 Mpa,4.5Mpa, maximum stress of machine tool operation: 80 Mpa.
In some embodiments, the first simulated structure index performance is obtained after the machining condition of the machine tool is processed by the alternative machine tool performance simulation optimization model; correcting the simulation model through the polarization curve performance of the first machine tool cutting condition in the first simulated real cutting performance index, so that the relative error between the first simulated structure index performance and the first real cutting performance index
And when the ratio exceeds 20%, correcting part of the alternative structural indexes to obtain the fuzzy correction structural index.
The calculation shows that in the first wheel model correction process, the relative error between the simulation result of the first machine tool cutting machining condition and the real cutting machining performance index is 7.3%, and the corresponding compound motion deviation is about 21
。
Based on the parameters of the second cutting condition of the machine tool in the real cutting performance indexes, adjusting the fuzzy correction structure index to obtain a secondary correction structure index;
the static deformation of the whole bed and the structural part is respectively as follows: 45
，27
。
The composite motion deviation of the whole bed and the structural part is respectively as follows: 24
，1.3
。
The dynamic deformation of the whole bed and the structural part is respectively as follows: 137
，51
。
The maximum stress of the whole bed and the structural part is respectively as follows: 168 Mpa,3.2Mpa, maximum stress of machine tool operation: 75 Mpa.
Performing correction on the simulation structure index performance II under the cutting machining condition II of the machine tool based on the simulation model to obtain a model simulation result, and performing comparison with the real cutting machining performance index II to obtain a relative error between the simulation structure index performance II and the real cutting machining performance index II;
in some embodiments, it is calculated that during the first round of model modification, the relative error between the second simulated structural indicator performance and the second simulated true machinability indicator is 22.7%, and the corresponding compound motion deviation is about 23%
。
Because the relative error between the simulated structure index performance II and the real cutting performance index II in the machine tool cutting machining condition II exceeds 20%, verification and correction need to be executed on the machine tool cutting machining condition I and the machine tool cutting machining condition II again.
The calculation results show that in the second wheel model correction process, the relative error between the first simulated structure index performance and the first real cutting machining performance index is 4.3%, the relative error between the second simulated structure index performance and the second real cutting machining performance index is 26.2%, and verification and correction need to be performed on the first machine tool cutting machining condition and the second machine tool cutting machining condition again.
The calculation results show that in the third model correction process, the relative error between the first simulated structure index performance and the first real cutting performance index is 4.9%, the relative error between the second simulated structure index performance and the second real cutting performance index is 20.4%, and verification and correction need to be performed on the first machine tool cutting condition and the second machine tool cutting condition again.
The calculation shows that in the fourth wheel model correction process, the relative error between the first simulation structure index performance and the first real cutting performance index is 2.9%, the relative error between the second simulation structure index performance and the second real cutting performance index is 23.1%, and verification and correction need to be carried out on the first machine tool cutting condition and the second machine tool cutting condition again.
Comparing the second real cutting performance index with the second simulated structure index, and determining the relative error between the second simulated structure index and the second real cutting performance index
When the quantity exceeds 20 percent, setting parameters needing to be corrected in the alternative machine tool performance simulation optimization model as secondary correction structural indexes, and correcting the secondary correction structural indexes again based on the machine tool cutting machining conditions until the secondary correction structural indexes are corrected again until the quantity exceeds 20 percent
Not more than 20% and
and (5) finishing correction to obtain a corrected machine tool simulation model, wherein the correction does not exceed 20%.
Machine tool cutting conditions two
And
the calculation expression of (a) is as follows:
in some embodiments, it is calculated that during the fifth round of model modificationThe relative error between the simulation structure index I and the real cutting processing performance index I is 5.6%, and the corresponding compound motion deviation is about 20 at the moment
. The relative error between the second simulation structure index performance and the second real cutting processing performance index is 6.8 percent, and the corresponding composite motion deviation is about 16
。
Specifically, step (4) is based on correcting the machine tool simulation model, and machine tool simulation analysis is respectively executed under P cutting machining conditions to obtain P optimized structural indexes:
the number of P is a × b × c × d;
the values of the selected static deformation horizontal value, the selected dynamic deformation horizontal value, the selected maximum stress and the selected composite motion deviation are respectively as follows:
the preferred cutting conditions satisfy the following conditions:
in some embodiments, splitting processing is performed on cutting conditions of a machine tool to obtain a plurality of atomic cutting conditions, and machine tool simulation analysis is performed on the plurality of atomic cutting conditions based on a corrected machine tool simulation model to obtain P optimized structural indexes; based on the testing and simulation requirements of the machine tool,setting a reasonable value range of cutting conditions in simulation analysis, wherein the reasonable value range of the dynamic deformation is [40 ]
，130
]The reasonable value range of the static deformation is [20 ]
，78
]The maximum stress is in the range of [3Mpa,170Mpa]The value of the composite motion deviation of the structural member and the whole bed is determined as 2
，19
。
By means of uniform distribution, 5 dynamic deformation levels, 50 for each level, were selected
，60
，70
，80
，90
。
DSHAPEx2={50
，60
，70
，80
，90
}
By means of uniform distribution, 4 static variation levels, 25 respectively, are selected
，28
，30
，35
。
Mx1={25
，28
，30
，35
}
Through the mode of uniform distribution, 2 values of the maximum stress are selected, wherein the values are 70Mpa and 140Mpa respectively.
Tx3={70Mpa，140Mpa}
The total number of the cutting conditions was 40 sets by the full array combination.
And carrying out simulation analysis on the machine tool under the 40 groups of cutting machining conditions to obtain a model output result.
In some embodiments, the machine tool performance simulation fuzzy evaluation method in the step (5) is expressed in the expressiond，e，fRespectively represent fuzzy evaluation weight factors, and the numerical values of the fuzzy evaluation weight factors are respectively 1/3,1/3 and 1/3.
And (4) calculating to obtain a numerical value of the performance simulation fuzzy evaluation method based on the model output results under the 40 groups of cutting machining conditions.
And selecting the corresponding cutting condition with the maximum optimized structure index evaluation value based on the calculation result of the fuzzy evaluation method for machine tool performance simulation, and defining the corresponding cutting condition as a preferred cutting condition.
In some embodiments, it is calculated that there are two sets of preferred machining conditions, the first set being the dynamic deformation 90
Amount of static deformation 35
Maximum stress 70MPa, second group is dynamic deformation 80
Amount of static deformation 35
Maximum stress 140MPa.
Specifically, in some embodiments, the machine tool is placed on the machine tool turret in step (6), and gas supply pipes, electronic loads, and the like are connected.
And after the rigidity of the stand-by machine tool is detected to be qualified, setting the test cutting condition of the turntable according to the parameters of the preferred cutting condition, and testing the machine tool to obtain a relation graph between the structural index design and the deformation of the machine tool.
In the embodiment, through the mutual coupling of the simulation means and the test means, the test quantity and the test period required in the process of optimizing the cutting conditions of the machine tool can be reduced, the reliability and the accuracy of the simulation result can be improved, the effect of the simulation means in the optimization process can be better played, and finally the improvement of the performance of the machine tool can be realized with lower test cost and shorter research and development period.
The performance under the preferred cutting machining condition is respectively improved by 8.4% and 9.7% compared with the performance under the machine tool cutting machining condition according to the numerical value of the machine tool performance simulation fuzzy evaluation method.
The calculation shows that under the preferred cutting condition, the relative errors between the results of the machine tool simulation model and the actual cutting performance indexes are respectively 6.1% and 6.9%.
In addition, in response to the performance optimization method, referring to fig. 3, according to a second embodiment, the invention claims a machine tool simulation optimization design system based on fuzzy evaluation, which is characterized by comprising:
the alternative simulation optimization model building module: constructing an alternative machine tool performance simulation optimization model, and obtaining an alternative structure index through the alternative machine tool performance simulation optimization model;
an operation monitoring module: the method comprises the steps of monitoring the operation of a machine tool to obtain a plurality of real cutting performance indexes of the machine tool under a plurality of cutting conditions of the machine tool;
a correction module: correcting the machine tool simulation model according to the real cutting performance indexes to obtain a corrected machine tool simulation model;
a simulation splitting module: splitting the plurality of machine tool cutting conditions to obtain a plurality of atomic cutting conditions, and performing machine tool simulation analysis on the plurality of atomic cutting conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes;
a first-choice evaluation module: constructing a machine tool performance simulation fuzzy evaluation method, and respectively inputting the P optimized structure indexes into the machine tool performance simulation fuzzy evaluation method to obtain the optimized structure index with the highest evaluation value, wherein the atomic cutting processing condition corresponding to the optimized structure index with the highest evaluation value is used as a preferred cutting processing condition;
an optimization and verification module: according to the first-choice cutting machining condition, performing operation monitoring to obtain a first-choice real cutting machining performance index of the machine tool, and performing comparison between the first-choice real cutting machining performance index and an optimized structure index with the highest evaluation value to obtain a structure index design optimization result of the machine tool;
the alternative machine tool performance simulation optimization model comprises a static performance simulation optimization model, a dynamic performance simulation optimization model and a thermal deformation performance simulation optimization model, and the alternative structure index is obtained based on the static performance simulation optimization model, the dynamic performance simulation optimization model and the thermal deformation performance simulation optimization model;
the static performance simulation optimization model is characterized as follows:
in the expression (2), i represents a turntable,
the lead of the lead screw is shown,
the radial bearing bore area is shown as,
which represents the density of the material and is,
the diameter of the guide rail is shown,
representing the coefficient of elasticity of the material, t representing the number of oil pads,
which represents the load of the ring gear,
represents the cutting force; the expression (2) is suitable for a heavy machine tool;
the dynamic performance simulation optimization model is characterized as follows:
in expressions (3) and (4)
Shows the density of main structural parts (ram, ram seat, column, slide seat and bed), RV shows the elasticity modulus of the veneering at the main junction surface (bed slide seat junction surface, column ram seat junction surface and ram seat ram junction surface),
the static and dynamic stiffness of the whole machine is shown,
the maximum deformation of the whole machine is shown, t is the number of oil pads,
the maximum deformation of the end of the spindle is indicated,
representing the natural frequency of the front stage of the whole machine;
the lead of the lead screw is shown,
the rigidity of the nut pair is shown,
the radial bearing bore area is shown as,
the position loop gain is shown as a function of,
the gain of the speed loop is shown as,
the average milling force is expressed in terms of,
represents the feed rate;
the thermal deformation performance simulation optimization model is characterized as follows:
in expression (5)
Indicating the cooling rate, T the reference temperature, T the number of oil pads,
the maximum temperature is indicated and is,
the cut-off temperature is indicated.
Further, the operation monitoring of the machine tool is performed to obtain a plurality of real cutting performance indexes of the machine tool under a plurality of cutting conditions of the machine tool, and the method specifically comprises the following steps:
setting a first machine tool cutting condition and a second machine tool cutting condition of a machine tool;
respectively executing operation monitoring on the machine tool according to the first machine tool cutting condition and the second machine tool cutting condition to obtain a first real cutting performance index and a second real cutting performance index;
the method for correcting the alternative machine tool performance simulation optimization model according to the multiple real cutting machining performance indexes to obtain a corrected machine tool simulation model specifically comprises the following steps:
setting part of alternative structure indexes to be corrected in an alternative machine tool performance simulation optimization model based on the first machine tool cutting condition;
obtaining a first simulation structure index performance after the machine tool cutting machining condition is processed by an alternative machine tool performance simulation optimization model;
comparing the first true cutting performance index with the first simulated structure index, and determining the relative error between the first simulated structure index and the first true cutting performance index
When the ratio exceeds 20%, correcting part of the alternative structural indexes to obtain fuzzy correction structural indexes;
based on the second cutting machining condition of the machine tool, adjusting the fuzzy correction structure index to obtain a secondary correction structure index;
the second machine tool cutting machining condition is processed by the alternative machine tool performance simulation optimization model to obtain a second simulation structure index performance;
comparing the second true cutting performance index with the second simulated structure index, and comparing the second simulated structure index with the second true cutting performance index when the relative error exists between the second simulated structure index and the second true cutting performance index
When the rate of change exceeds 20%, setting parameters needing to be corrected in the alternative machine tool performance simulation optimization model as secondary correction structure indexes, and correcting the secondary correction structure indexes again based on machine tool cutting conditions until the secondary correction structure indexes are corrected again until the rate of change is higher than 20%
Not more than 20% and
and if not more than 20%, finishing correction to obtain a corrected machine tool simulation model.
Further, splitting a plurality of machine tool cutting conditions to obtain a plurality of atomic cutting conditions, performing machine tool simulation analysis on the plurality of atomic cutting conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes, specifically comprising:
setting a reasonable value range of machine tool cutting conditions according to a reasonable value range of static deformation [ SSHAPEmin, SSHAPEmax ], a reasonable value range of dynamic deformation [ DSHAPEmin, DSHAPEmax ], a reasonable value range of maximum stress [ Forcemin, forcemax ], a reasonable value range of compound motion deviation [ MoveDemin, moveDemax ];
based on the reasonable value range of the machine tool cutting machining conditions, selecting SSHAPE static deformation values, dy dynamic deformation values, fmax maximum stress values and MoveDe composite motion deviation values in an evenly distributed mode to obtain P atom cutting machining conditions, wherein the SSHAPE, the Dy, the Fmax and the MoveDe are positive integers;
and respectively executing machine tool simulation analysis under P atom cutting machining conditions based on the corrected machine tool simulation model to obtain P optimized structure indexes.
Further, a machine tool performance simulation fuzzy evaluation method is constructed, the P optimized structure indexes are respectively input into the machine tool performance simulation fuzzy evaluation method, the optimized structure index with the highest evaluation value is obtained, and the atomic cutting processing condition corresponding to the optimized structure index with the highest evaluation value serves as a preferred cutting processing condition, and the method specifically comprises the following steps:
constructing a machine tool performance simulation fuzzy evaluation method, and obtaining P optimized structure index evaluation values based on P optimized structure indexes;
setting the optimized structure index corresponding to the highest evaluation value in the evaluation values of the P optimized structure indexes as the optimized structure index with the highest evaluation value, and taking the atomic cutting condition corresponding to the optimized structure index with the highest evaluation value as the preferred cutting condition,
wherein the static deformation horizontal value of the first-choice cutting machining condition is Mx1, the dynamic deformation horizontal value is DSHAPEx2, the maximum stress is Tx3, and the compound motion deviation is Px4;
machine tool performance simulationFuzzy evaluation methodFuzzyNetThe expression is as follows:
wherein,
the degree of membership is represented by,
，
，
respectively representing low deformation, medium deformation and high deformation, the numerical values of which are determined according to the P optimized structure indexes,m，n，prespectively representing fuzzy evaluation weight factors, the numerical values of which are reasonable value ranges [0, 1%]Positive real numbers of (d);
the preferred cutting conditions satisfy the following conditions:
unless defined otherwise, technical or scientific terms used herein shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs. The use of "first," "second," and the like, herein does not denote any order, quantity, or importance, but rather the terms "first," "second," and the like are used to distinguish one element from another. The terms "connected" or "coupled" and the like are not restricted to actual or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships are changed accordingly.
The foregoing is a preferred embodiment of the present invention, and it should be noted that it would be apparent to those skilled in the art that various modifications and enhancements can be made without departing from the principles of the invention, and such modifications and enhancements are also considered to be within the scope of the invention.
Claims (2)
1. A machine tool simulation optimization design method based on fuzzy evaluation is characterized by comprising the following steps:
constructing a performance simulation optimization model of an alternative machine tool, and obtaining an alternative structure index through the performance simulation optimization model of the alternative machine tool;
performing operation monitoring on the machine tool to obtain a plurality of real cutting machining performance indexes of the machine tool under a plurality of machine tool cutting machining conditions;
correcting the alternative machine tool performance simulation optimization model according to the real cutting machining performance indexes to obtain a corrected machine tool simulation model;
splitting the plurality of machine tool cutting conditions to obtain a plurality of atomic cutting conditions, and performing machine tool simulation analysis on the plurality of atomic cutting conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes;
constructing a machine tool performance simulation fuzzy evaluation method, and respectively inputting the plurality of optimized structure indexes into the machine tool performance simulation fuzzy evaluation method to obtain the optimized structure index with the highest evaluation value, wherein the atomic cutting processing condition corresponding to the optimized structure index with the highest evaluation value is used as a preferred cutting processing condition;
executing the operation monitoring according to the preferred cutting machining condition to obtain a preferred real cutting machining performance index of the machine tool, and comparing the preferred real cutting machining performance index with the optimized structure index with the highest evaluation value to obtain a structure index design optimization result of the machine tool;
the alternative machine tool performance simulation optimization model comprises a static performance simulation optimization model, a dynamic performance simulation optimization model and a thermal deformation performance simulation optimization model, and the alternative structure index is obtained based on the static performance simulation optimization model, the dynamic performance simulation optimization model and the thermal deformation performance simulation optimization model;
the static performance simulation optimization model is characterized as follows:
in the expression (2), i represents a turntable,
the lead of the lead screw is shown,
the radial bearing bore area is shown as,
which represents the density of the material and is,
the diameter of the guide rail is shown,
representing the coefficient of elasticity of the material, t representing the number of oil pads,
which represents the load of the ring gear,
represents the cutting force; the expression (2) is suitable for a heavy machine tool;
the dynamic performance simulation optimization model is characterized as follows:
in expressions (3) and (4)
Shows the density of main structural parts including ram, ram seat, column, slide seat and bed, RV shows the main combination surface including bed slide seat combination surface, column ram seat combination surface and facing elastic modulus at ram seat and ram combination surface,
the static and dynamic stiffness of the whole machine is shown,
the maximum deformation of the whole machine is shown, t is the number of oil pads,
which represents the maximum deformation of the end of the spindle,
representing the natural frequency of the front stage of the whole machine;
the lead of the lead screw is shown,
the rigidity of the nut pair is shown,
diameter of the displayThe area of the bearing hole is opposite to the area of the bearing hole,
the position loop gain is shown as a function of,
the gain of the speed loop is shown as,
the average milling force is expressed in terms of,
represents the feed rate;
the thermal deformation performance simulation optimization model is characterized as follows:
in expression (5)
Indicating the cooling rate, T the reference temperature, T the number of oil pads,
the maximum temperature is indicated and is,
denotes the cut-off temperature;
the method comprises the following steps of monitoring the operation of a machine tool to obtain a plurality of real cutting performance indexes of the machine tool under a plurality of cutting conditions of the machine tool, and specifically comprises the following steps:
setting a first machine tool cutting condition and a second machine tool cutting condition of a machine tool;
respectively executing operation monitoring on the machine tool according to the first machine tool cutting condition and the second machine tool cutting condition to obtain a first real cutting performance index and a second real cutting performance index;
correcting the alternative machine tool performance simulation optimization model according to a plurality of real cutting machining performance indexes to obtain a corrected machine tool simulation model, which specifically comprises the following steps:
setting part of alternative structure indexes needing to be corrected in the alternative machine tool performance simulation optimization model based on the first machine tool cutting condition;
obtaining a first simulation structure index performance after the machine tool cutting machining condition is processed by an alternative machine tool performance simulation optimization model;
comparing the first true machinability index with the first simulated structure index, and comparing the relative error between the first simulated structure index and the first true machinability index
When the ratio exceeds 20%, correcting part of the alternative structural indexes to obtain fuzzy correction structural indexes;
based on the second cutting condition of the machine tool, adjusting the fuzzy correction structure index to obtain a secondary correction structure index;
the second machine tool cutting machining condition is processed by the alternative machine tool performance simulation optimization model to obtain a second simulation structure index performance;
comparing the second true cutting performance index with the second simulated structure index, and comparing the second simulated structure index with the second true cutting performance index when the relative error exists between the second simulated structure index and the second true cutting performance index
When the rate of change exceeds 20%, setting parameters needing to be corrected in the alternative machine tool performance simulation optimization model as secondary correction structure indexes, and correcting the secondary correction structure indexes again based on machine tool cutting conditions until the secondary correction structure indexes are corrected again until the rate of change is higher than 20%
Not more than 20% and
finishing correction to obtain a corrected machine tool simulation model when the correction does not exceed 20%;
the splitting processing is executed on the plurality of machine tool cutting conditions to obtain a plurality of atomic cutting conditions, and machine tool simulation analysis is executed on the plurality of atomic cutting conditions based on the corrected machine tool simulation model to obtain P optimized structure indexes, which specifically comprises:
setting a reasonable value range of the cutting and processing conditions of the machine tool according to a reasonable value range of the static deformation [ SSHAPEmin, SSHAPEmax ], a reasonable value range of the dynamic deformation [ DSHAPEmin, DSHAPEmax ], a reasonable value range of the maximum stress [ Forcemin, forcemax ], a reasonable value range of the compound motion deviation [ MoveDemin, moveDemax ];
on the basis of the reasonable value range of the machine tool cutting machining conditions, selecting a values of the static deformation, b values of the dynamic deformation, c values of the maximum stress and d values of the compound motion deviation in an evenly distributed mode to obtain P atomic cutting machining conditions, wherein a, b, c and d are positive integers;
respectively executing machine tool simulation analysis under the P atomic cutting machining conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes;
the method for establishing the fuzzy evaluation method for machine tool performance simulation and inputting the plurality of optimized structure indexes into the fuzzy evaluation method for machine tool performance simulation respectively to obtain the optimized structure index with the highest evaluation value, wherein the atomic cutting processing condition corresponding to the optimized structure index with the highest evaluation value serves as a preferred cutting processing condition, and specifically comprises the following steps:
constructing a machine tool performance simulation fuzzy evaluation method, and obtaining P optimized structure index evaluation values based on P optimized structure indexes;
setting the optimized structure index corresponding to the highest evaluation value among the P optimized structure index evaluation values as the optimized structure index with the highest evaluation value, and setting the atomic machining condition corresponding to the optimized structure index with the highest evaluation value as a preferred machining condition,
wherein the static deformation level value of the preferred cutting machining condition is Mx1, the dynamic deformation level value is DSHAPEx2, the maximum stress is Tx3, and the compound motion deviation is Px4;
the machine tool performance is imitatedTrue fuzzy evaluation methodFuzzyNetThe expression is as follows:
wherein,
the degree of membership is represented by,
，
，
respectively representing low deformation, medium deformation and high deformation, the numerical values of which are determined according to the P optimized structure indexes,m，n，prespectively representing fuzzy evaluation weight factors, the numerical values of which are reasonable value ranges [0, 1%]Positive real numbers of (d);
the preferred cutting conditions satisfy the following conditions:
2. a machine tool simulation optimization design system based on fuzzy evaluation is characterized by comprising:
the alternative simulation optimization model building module: constructing an alternative machine tool performance simulation optimization model, and obtaining an alternative structure index through the alternative machine tool performance simulation optimization model;
an operation monitoring module: performing operation monitoring on the machine tool to obtain a plurality of real cutting machining performance indexes of the machine tool under a plurality of machine tool cutting machining conditions;
a correction module: correcting the alternative machine tool performance simulation optimization model according to the real cutting machining performance indexes to obtain a corrected machine tool simulation model;
a simulation splitting module: splitting the plurality of machine tool cutting conditions to obtain a plurality of atomic cutting conditions, and performing machine tool simulation analysis on the plurality of atomic cutting conditions based on the corrected machine tool simulation model to obtain P optimized structure indexes;
a first-choice evaluation module: constructing a machine tool performance simulation fuzzy evaluation method, and respectively inputting the P optimized structure indexes into the machine tool performance simulation fuzzy evaluation method to obtain the optimized structure index with the highest evaluation value, wherein the atomic cutting processing condition corresponding to the optimized structure index with the highest evaluation value is used as a preferred cutting processing condition;
an optimization and verification module: executing the operation monitoring according to the preferred cutting machining condition to obtain a preferred real cutting machining performance index of the machine tool, and comparing the preferred real cutting machining performance index with the optimized structure index with the highest evaluation value to obtain a structure index design optimization result of the machine tool;
the alternative machine tool performance simulation optimization model comprises a static performance simulation optimization model, a dynamic performance simulation optimization model and a thermal deformation performance simulation optimization model, and the alternative structure index is obtained based on the static performance simulation optimization model, the dynamic performance simulation optimization model and the thermal deformation performance simulation optimization model;
the static performance simulation optimization model is characterized as follows:
in the expression (2), i represents a turntable,
the lead of the lead screw is shown,
the radial bearing bore area is shown as,
which represents the density of the material and is,
the diameter of the guide rail is shown,
representing the coefficient of elasticity of the material, t representing the number of oil pads,
which represents the load of the ring gear,
represents the cutting force; the expression (2) is suitable for a heavy machine tool;
the dynamic performance simulation optimization model is characterized as follows:
in expressions (3) and (4)
The density of main structural members including ram, ram seat, column, slide seat and lathe bed, RV represents main joint surface including lathe bed slide seat joint surface and column ram seatThe elastic modulus of the veneers at the joint surface and the joint surface of the ram seat and the ram,
the static and dynamic stiffness of the whole machine is shown,
the maximum deformation of the whole machine is shown, t is the number of oil pads,
which represents the maximum deformation of the end of the spindle,
representing the natural frequency of the front stage of the whole machine;
the lead of the lead screw is shown,
the stiffness of the nut pair is shown,
the radial bearing bore area is shown as,
the position loop gain is shown as a function of,
the gain of the speed loop is shown,
the average milling force is shown as a function of,
represents the feed speed;
the thermal deformation performance simulation optimization model is characterized as follows:
in expression (5)
Indicating the cooling rate, T the reference temperature, T the number of oil pads,
the maximum temperature is indicated and is,
denotes the cut-off temperature;
the performing operation monitoring on the machine tool to obtain a plurality of real cutting performance indexes of the machine tool under a plurality of cutting conditions of the machine tool specifically comprises:
setting a first machine tool cutting condition and a second machine tool cutting condition of the machine tool;
performing operation monitoring on the machine tool according to the first machine tool cutting condition and the second machine tool cutting condition respectively to obtain a first real cutting performance index and a second real cutting performance index;
the method for correcting the alternative machine tool performance simulation optimization model according to the plurality of real cutting machining performance indexes to obtain a corrected machine tool simulation model specifically comprises the following steps:
setting part of the alternative structure indexes to be corrected in the alternative machine tool performance simulation optimization model based on the first machine tool cutting condition;
obtaining a first simulation structure index performance after the machine tool cutting machining condition is processed by the alternative machine tool performance simulation optimization model;
comparing the first true cutting performance index with the first simulated structure index, and determining the relative error between the first simulated structure index and the first true cutting performance index
When the ratio exceeds 20%, correcting the partial alternative structure indexes to obtain a fuzzy correction nodeConstructing an index;
based on the second cutting condition of the machine tool, adjusting the fuzzy correction structure index to obtain a secondary correction structure index;
the second machine tool cutting machining condition is processed by the alternative machine tool performance simulation optimization model to obtain a second simulation structure index performance;
comparing the second real cutting performance index with the second simulated structure index, and determining the relative error between the second simulated structure index and the second real cutting performance index
When the quantity exceeds 20%, setting parameters needing to be corrected in the alternative machine tool performance simulation optimization model as the secondary correction structure indexes, and correcting the secondary correction structure indexes again on the basis of the machine tool cutting machining conditions until the secondary correction structure indexes are corrected again until the machine tool cutting machining conditions are met
Not more than 20% and said
Finishing correction to obtain the corrected machine tool simulation model, wherein the correction does not exceed 20%;
the splitting processing is executed on the plurality of machine tool cutting conditions to obtain a plurality of atomic cutting conditions, and machine tool simulation analysis is executed on the plurality of atomic cutting conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes, which specifically includes:
setting a reasonable value range of the cutting and processing conditions of the machine tool according to a reasonable value range of the static deformation [ SSHAPEmin, SSHAPEmax ], a reasonable value range of the dynamic deformation [ DSHAPEmin, DSHAPEmax ], a reasonable value range of the maximum stress [ Forcemin, forcemax ], a reasonable value range of the compound motion deviation [ MoveDemin, moveDemax ];
on the basis of the reasonable value range of the machine tool cutting machining conditions, selecting a values of the static deformation, b values of the dynamic deformation, c values of the maximum stress and d values of the compound motion deviation in an evenly distributed mode to obtain P atomic cutting machining conditions, wherein a, b, c and d are positive integers;
respectively executing machine tool simulation analysis under the P atomic cutting machining conditions based on the corrected machine tool simulation model to obtain P optimized structural indexes;
the method for establishing the fuzzy evaluation method for machine tool performance simulation and inputting the plurality of optimized structure indexes into the fuzzy evaluation method for machine tool performance simulation respectively to obtain the optimized structure index with the highest evaluation value, wherein the atomic cutting processing condition corresponding to the optimized structure index with the highest evaluation value serves as a preferred cutting processing condition, and specifically comprises the following steps:
constructing a machine tool performance simulation fuzzy evaluation method, and obtaining P optimized structure index evaluation values based on P optimized structure indexes;
setting the optimized structure index corresponding to the highest evaluation value among the P optimized structure index evaluation values as the optimized structure index with the highest evaluation value, and setting the atomic machining condition corresponding to the optimized structure index with the highest evaluation value as a preferred machining condition,
wherein the static deformation level value of the preferred cutting processing condition is Mx1, the dynamic deformation level value is DSHAPEx2, the maximum stress is Tx3, and the compound motion deviation is Px4;
fuzzy evaluation method for machine tool performance simulationFuzzyNetThe expression is as follows:
wherein,
and represents the degree of membership,
，
，
respectively representing low deformation, medium deformation and high deformation, the numerical values of which are determined according to the P optimized structure indexes,m，n，prespectively representing fuzzy evaluation weight factors, the values of which are reasonable value ranges [0,1 ]]Positive real numbers of (d);
the preferred cutting conditions satisfy the following conditions:
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