CN104216334A - Selection optimization method of temperature measurement point combination for positioning errors of numerically-controlled machine tool under thermal effect - Google Patents
Selection optimization method of temperature measurement point combination for positioning errors of numerically-controlled machine tool under thermal effect Download PDFInfo
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Abstract
The invention provides a selection optimization method of a temperature measurement point combination for positioning errors of a numerically-controlled machine tool under thermal effect. The selection optimization method is capable of identifying the influence of the temperature measurement point in each position on the positioning errors of the machine tool based on a grey correlation policy and a rough set theory. The selection optimization method comprises the following steps: k temperature sensors are mounted in special positions of the machine tool to measure the real-time temperature values, changing over time, of the machine tool during operation, and meanwhile, a laser interferometer is used for measuring positioning error values affected by temperatures; n sensitive temperature measurement point positions are screened out by use of the grey correlation policy; the positioning errors and the temperature data of the machine tool are preprocessed according to the principle of the rough set theory and a policy table is established; m feasible temperature point combinations are obtained by use of rough set reduction software; the optimal temperature measurement point combination of the machine tool is identified by virtue of comprehensive analysis. The selection optimization method of the temperature measurement point combination for the positioning errors of the numerically-controlled machine tool under the thermal effect is capable of solving the problem of excessive temperature measurement points or poor compensation model robustness in the positioning error compensation modeling process of the numerically-controlled machine tool.
Description
Technical field
The present invention relates to the optimization method of the measurement of lathe positioning error in a kind of Computerized Numerical Control Cutting Processes and error compensation modeling temperature variable combination used, belong to NC Machine Error analysis technical field.
Background technology
Position accuracy for CNC machine tools is the moving component positional precision that motion can reach under digital control system controls of lathe, in general, just refers to that lathe navigates to the order of accuarcy of impact point in program the point of a knife of cutter.Machine finish is finally to be fixed a cutting tool by lathe and relative displacement between workpiece determines.Therefore positioning error is reduced most important to the machining precision improving lathe.
Machine tool error penalty method becomes current topmost raising precision, reduces the means of error because its good economy performance, feasibility are high.And set up the key link that positioning error forecast model is error compensation, the form of model and accuracy directly affect speed and the effect of error compensation.Set up positioning error forecast model accurately and must obtain the lathe Temperature Distribution relevant to positioning error, this just needs each position on lathe to arrange a large amount of temperature sensors, the real time temperature distribution be used in measuring machine bed operating process.In general, in heat error compensation temperature point selection from hundreds of to several not etc.
But temperature point too much not only makes the workload of arranging measuring point strengthen, and temperature point arranges that get Tai Mi also can make the output signal of adjacent measuring point have larger correlativity, affects computational accuracy on the contrary.So, select several key temperatures measuring point to realize accurate positioning error modeling and just to seem particular importance, but how selective temperature measuring point is one of key issue in the modeling of lathe positioning error and compensation technique.
Summary of the invention
The object of the invention is to for existing issue, based on rough set theory, on the basis of gray relative strategy, the significance level that each temperature point in the field distribution of analytical engine bed tempertaure affects machine tooling positioning error, propose, according to Rough Set Analysis software (ROSETTA), yojan is carried out to lathe temperature, error information, and the comprehensive sensor combinations found out positioning error impact several measurement points responsive especially of analyzing reaches the object optimizing lathe positioning error temperature point, namely finds out the combination of Optimal Temperature measuring point.
For achieving the above object, the technical solution used in the present invention is a kind of selection optimization method about positioning error temperature point combination under numerically-controlled machine thermal effect, for solving during digital control machine tool positioning error compensates the technical matters how optimizing temperature point combination.
The concrete steps of the method are as follows,
Step 1, gathers time dependent temperature variable and positioning error amount in numerically-controlled machine operational process;
First, install k temperature sensor in the critical positions of numerically-controlled machine and carry out temperature survey, the critical positions of described numerically-controlled machine mainly comprises the exemplary position of front-end of spindle and rear end, spindle box body front and back end and upper end, three axial filament thick stick motor, bearing, guide rail, operating position.Laser interferometer is fixed on and lathe carries out positioning error measurement and generating laser and be fixed on receiver on guide rail and be fixed on lathe cutter saddle;
Then, first measurement and positioning error under lathe cold conditions (i.e. just start), after measurement, quick moving movement axle makes lathe temperature raise, and then measure, again temperature rise so repeat to tend towards stability to each temperature variation of lathe, namely lathe reach thermal equilibrium state terminate measure.Can obtain by running lathe: the 1. variable quantity T{T of the temperature T that records of the temperature sensor of k position t in time
1(t), T
2(t) ..., T
k(t) }; 2. lathe positioning error amount Y (t) that records of laser interferometer;
Step 2, application grey correlation analysis filters out m sensitive temperature point position:
Utilize grey correlation analysis to set up reference sequence (positioning error data) and compare the correlation coefficient ξ between ordered series of numbers (k temperature point data)
0kwith degree of association γ
0k, and these degrees of association be arranged in order from big to small, what represent that these point position temperature variation produce positioning error to lathe respectively affects size; Set a threshold gamma ', in general, definition threshold value be:
as correlation coefficient value γ
0kbe greater than γ ' time, temperature point position is retained; And the temperature variation of all the other positions is very small on positioning error impact, all cast out, by k temperature point be successfully reduced to m individual responsive measuring point T ' T '
1(t), T '
2(t) ..., T '
m(t) }.
Step 3, according to the principle of rough set theory, carries out pre-service to positioning error under lathe thermal effect and temperature data, forms a decision table;
Using the temperature of surveyed a k position as conditional attribute C, i.e. C={T
1(t), T
2(t) ..., T
k(t) }, the positioning error displacement of surveying attribute D, i.e. D={Y (t) as a result }, thus establish a system decision-making table K=(U, C ∪ D), and this decision table is established as an Excel table.
Step 4, utilizes Rough Set Analysis software (ROSETTA) to draw the individual feasible temperature point combination of n:
By the system decision-making table K=(U set up above, C ∪ D) Excel table be input in Rough Set Analysis software (ROSETTA) and go, by carrying out Data Reduction process after Data-parallel language, Data Discretization, obtain the temperature point combination that n kind is feasible, the combination of these temperature points can intactly express machine tool temperature field distribution situation.
Step 5, comprehensive identifier bed Optimal Temperature measuring point of analyzing combines, and completes selection optimization method:
M sensitive temperature measuring point of Integrated comparative yojan and n temperature point combination, filter out and comprise the temperature point combination that sensitive temperature measuring point is maximum and the degree of association is the highest, is required Optimal Temperature measuring point combination.
Compared with prior art, the invention has the beneficial effects as follows: the present invention is on the basis measuring numerically-controlled machine temperature field and positioning error, gray relative Policy Filtering is utilized to go out the sensor layout points that m is individual and lathe positioning error correlativity is high, again temperature data and positioning error data are established as decision table according to rough set theory, by Rough Set Analysis software (ROSETTA), yojan is optimized to decision table afterwards, draws n feasibility temperature point combination; Find out the combination of Optimal Temperature measuring point finally by comprehensive analysis, determine the installation site that several sensor layout points compensates as the modeling of lathe positioning error.Compare traditional method being found lathe key temperatures location point based on engineering judgement by great many of experiments number of times, the present invention have time-saving and efficiency, save temperature sensor, simplify modeling process, the robustness of lathe Model of locating error and accuracy advantages of higher.
Accompanying drawing explanation
Fig. 1 is workflow diagram of the present invention;
Fig. 2 is that numerically controlled lathe schematic diagram and temperature sensor thermometric arrange schematic diagram;
Fig. 3 is that numerically controlled lathe positioning error measures layout schematic diagram;
In figure: 1, the generating laser of laser interferometer, 2, the main shaft of lathe, 3, worktable, 4, the receiver of laser interferometer.
Embodiment
Below in conjunction with accompanying drawing and implementation process, the present invention is described further.
As Figure 1-3, the selection optimization method of lathe location error compensation modeling temperature point of the present invention, it is a kind of comprehensive selection method based on grey correlation analysis and rough set theory, realizes according to following steps:
First the correlative factor producing positioning error under thermal effect is considered, comprise the impact that the to-and-fro movement of machine tool motion part produces heat, motor running heating, each parts heat-generation and heat of lathe and environment temperature, analyze the position determining sensor in harvester bed tempertaure data experiment according to this.As shown in table 1,29 sensor positions refer to table 1: be numbered 1,2,3,4,6,8,14 and No. 18 sensor and be arranged in the exemplary position of front-end of spindle and rear end, each four of rear end, front end, and each transducer spacing is equal, is looped around on axle head; Sensor spacing is installed, and avoids the too near interference mutually of distance, not comprehensive apart from detection too far away, installs identical with lower sensor.5,7,11 and No. 15 are arranged on spindle box body front and back end and upper end, 12,19,21,22,24,28 and No. 29 are arranged on X, Y, Z tri-axial filament thick stick motor, bearing, shaft coupling and nut, 20,23,24,26 and No. 27 are arranged on X, Y, Z axis direction guiding rail, and 9,10,13,16 and No. 17 are arranged in vertical slide plate, worktable and environment temperature.
Table 1 29 sensor position tables
Laser interferometer is fixed on lathe, specifically installs as shown in Figure 3: the receiver 4 of the generating laser 1 of laser interferometer, the main shaft 2 of lathe, worktable 3, laser interferometer; First generating laser 1 is arranged on the smooth place of worktable 3 front end, afterwards the receiver 4 of laser interferometer is arranged on the main shaft 2 of lathe.Adjust the laser head of the generating laser 1 of laser interferometer after installation, make the axis of measurement axis and machine tool movement or parallel point-blank, harmonize by light path straight; During standby bed operating, on request the correlation parameter of lathe is measured.
Then run lathe and carry out data acquisition.The data that recycling grey correlation analysis collects, filter out the sensor layout points that m related coefficient is large.Then use Rough Set Analysis software (ROSETTA) to process temperature data and positioning error data, yojan is carried out to temperature point, obtain the individual feasible temperature point combination of n.Finally, the comprehensive temperature point combination analyzing m temperature sensitive point and n, filters out and comprises the temperature point combination that sensitive temperature measuring point is maximum and the degree of association is the highest, is required Optimal Temperature measuring point combination.
The specific implementation step of the present embodiment is:
Step 1, gathers time dependent temperature variable and positioning error amount in numerically-controlled machine operational process:
First, in the critical positions of numerically-controlled machine, k (can select from above-mentioned 29 temperature sensor location) temperature sensor is installed and carries out temperature survey, laser interferometer is fixed on lathe and carries out positioning error measurement (generating laser is fixed on guide rail, and receiver is fixed on lathe cutter saddle);
Then, first measurement and positioning error under lathe cold conditions (i.e. just start), after measurement, quick moving movement axle makes lathe temperature raise, and then measure, again temperature rise so repeat to tend towards stability to each temperature variation of lathe, namely lathe reach thermal equilibrium state terminate measure.Can obtain by running lathe: the temperature that 1. temperature sensor of k position records measures T{T over time
1(t), T
2(t) ..., T
k(t) }; 2. lathe positioning error amount Y (t) that records of laser interferometer;
Step 2, application grey correlation analysis filters out m sensitive temperature point position:
Grey System Analysis be according to characteristic parameter series each in system between the systematic analysis carried out of similar close degree mathematical theory.
In processing cutting process; lathe positioning error is obvious in the discontinuous point place change that lathe runs; selecting machine tool carrys out modeling analysis at the detected value of the material time Nodes of start, shutdown, also contemplates the even time interval of relational appraise to data acquisition simultaneously.Specifically, with certain node access time unit interval, l group (generally getting twenty or thirty group to be advisable) data can be got.
Due to implication and the object difference of each influence factor, thus desired value has different dimensions and data level usually, if the data between two sequences differ greatly in size, then the effect of fractional value sequence is easily covered by large sequence of values, for the ease of comparing, ensure that there is between each factor equivalence and same sequence, need process raw data, make it nondimensionalization and normalization.In general, just value conversion, equalization conversion and extreme difference usually can be adopted to convert three kinds of disposal routes to raw data.Here transform method is chosen according to corresponding requirements.
If reference sequence be positioning error data Y (t)=Y (j) | j=1,2 ..., l}, comparand is classified as k temperature point data T
i={ T
i(j) | i=i, 2 ..., k; J=1,2 ..., l}.Then Y (t) is to T
icorrelation coefficient at jth point:
In formula, Δ
0ij () is jth point Y (t) and T
ithe absolute value of (t), Δ
0i(j)=| Y (t)-T
i(t) |; min
imin
jΔ
0ij () is the two poles of the earth lowest difference; max
imax
jΔ
0ij () is the maximum difference in the two poles of the earth; ρ is resolution ratio, and ρ ∈ [0,1], generally gets ρ=0.5, in concrete operation, according to the degree of association between each data sequence, can adjust ρ value, to increase the resolution characteristic of comparative analysis.
Degree of association γ between two sequences
0ithe degree of association coefficient ξ in available two each moment of sequence
0ij the mean value of () calculates, that is,
In formula, it is the degree of association of subsequence i and auxiliary sequence; L is the data amount check of two comparative sequences.
Finally by the degree of association γ of each subsequence to same auxiliary sequence
0iby size order line up, namely form inteerelated order, it directly reflects each subsequence " primary and secondary " relation to same auxiliary sequence, namely represent these point position temperature variation on lathe produce positioning error affect size.Now, a threshold value is set
as correlation coefficient value γ
0kbe greater than γ ' time, temperature point position is retained, and all the other temperature point positions are then cast out, by k temperature point be successfully reduced to m responsive measuring point T ' T '
1(t), T '
2(t) ..., T '
m(t) }.
Establish a grey relational order by above-mentioned analytical calculation, γ is got to inteerelated order
0kbe greater than the factor of γ ', then have T
1> T
6> T
8> T
10> T
13> T
5> T
14> T
18> T
11> T
19.This grey relational order represents the arranging situation to the temperature point that positioning error has the greatest impact.
Step 3, according to the principle of rough set theory, carries out pre-service to positioning error under lathe thermal effect and temperature data, forms a decision table:
Using the temperature of surveyed a k position as conditional attribute C, i.e. C={T
1(t), T
2(t) ..., T
k(t) }, the positioning error displacement of surveying attribute D, i.e. D={Y (t) as a result }, thus establish a system decision-making table K=(U, C ∪ D), and this decision table is established as an Excel table.
Step 4, utilizes Rough Set Analysis software (ROSETTA) to draw the individual feasible temperature point combination of n:
By the system decision-making table K=(U set up above, C ∪ D) Excel table be input in Rough Set Analysis software (ROSETTA) and go, by carrying out Data Reduction process after Data-parallel language, Data Discretization, obtain the temperature point combination that n kind is feasible, the combination of these temperature points can than more completely expressing machine tool temperature field distribution situation.
Following feasible combination can be obtained through Rough Set Analysis software (ROSETTA) analysis:
{T
1T
5T
6T
8T
10T
13T
14}、{T
1T
6T
8T
10T
13T
14T
18}、{T
5T
6T
8T
10T
13T
14T
18}、{T
1T
5T
6T
8T
10T
11T
19}、{T
1T
5T
6T
8T
10T
13T
18}、{T
1T
5T
6T
8T
10T
13T
14T
18}。These six kinds of combinations can than more completely reacting whole numerically-controlled machine thermo parameters method situation and affecting situation to positioning error.
Step 5, comprehensive identifier bed Optimal Temperature measuring point of analyzing combines, and completes selection optimization method:
M sensitive temperature measuring point of Integrated comparative yojan and n temperature point combination, filter out and comprise the temperature point combination that sensitive temperature measuring point is maximum and the degree of association is the highest, is required Optimal Temperature measuring point combination.
By comparing grey relational order and temperature point combination, an Optimal Temperature measuring point combination can be drawn: { T
1, T
5, T
6, T
8, T
10, T
13, T
14.
After above-mentioned 5 steps complete, an optimum point position combination can be obtained, reach cost-saving, simplify the operation of location error compensation experiments of measuring and improve the object of robustness of Model of locating error.
Claims (4)
1., about a selection optimization method for positioning error temperature point combination under numerically-controlled machine thermal effect, it is characterized in that:
The concrete steps of the method are as follows,
Step 1, gathers time dependent temperature variable and positioning error amount in numerically-controlled machine operational process;
First, install k temperature sensor in the critical positions of numerically-controlled machine and carry out temperature survey, the critical positions of described numerically-controlled machine mainly comprises the exemplary position of front-end of spindle and rear end, spindle box body front and back end and upper end, three axial filament thick stick motor, bearing, guide rail, operating position; Laser interferometer is fixed on and lathe carries out positioning error measurement and generating laser and be fixed on receiver on guide rail and be fixed on lathe cutter saddle;
Then, first measurement and positioning error under lathe cold conditions, after measurement, quick moving movement axle makes lathe temperature raise, and then measure, again temperature rise so repeat to tend towards stability to each temperature variation of lathe, namely lathe reaches thermal equilibrium state and terminates measurement; Can obtain by running lathe: the 1. variable quantity T{T of the temperature T that records of the temperature sensor of k position t in time
1(t), T
2(t) ..., T
k(t) }; 2. lathe positioning error amount Y (t) that records of laser interferometer;
Step 2, application grey correlation analysis filters out m sensitive temperature point position:
Utilize grey correlation analysis to set up reference sequence and compare the correlation coefficient ξ between ordered series of numbers
0kwith degree of association γ
0k, and these degrees of association be arranged in order from big to small, what represent that these point position temperature variation produce positioning error to lathe respectively affects size; Set a threshold gamma ', in general, definition threshold value be:
as correlation coefficient value γ
0kbe greater than γ ' time, temperature point position is retained; And the temperature variation of all the other positions is very small on positioning error impact, all cast out, by k temperature point be successfully reduced to m individual responsive measuring point T ' T '
1(t), T '
2(t) ..., T '
m(t) };
Step 3, according to the principle of rough set theory, carries out pre-service to positioning error under lathe thermal effect and temperature data, forms a decision table;
Using the temperature of surveyed a k position as conditional attribute C, i.e. C={T
1(t), T
2(t) ..., T
k(t) }, the positioning error displacement of surveying attribute D, i.e. D={Y (t) as a result }, thus establish a system decision-making table K=(U, C ∪ D), and this decision table is established as an Excel table;
Step 4, utilizes Rough Set Analysis software (ROSETTA) to draw the individual feasible temperature point combination of n:
By the system decision-making table K=(U set up above, C ∪ D) Excel table be input in Rough Set Analysis software and go, by carrying out Data Reduction process after Data-parallel language, Data Discretization, obtain the temperature point combination that n kind is feasible, the combination of these temperature points can intactly express machine tool temperature field distribution situation;
Step 5, comprehensive identifier bed Optimal Temperature measuring point of analyzing combines, and completes selection optimization method:
M sensitive temperature measuring point of Integrated comparative yojan and n temperature point combination, filter out and comprise the temperature point combination that sensitive temperature measuring point is maximum and the degree of association is the highest, is required Optimal Temperature measuring point combination.
2. a kind of selection optimization method about positioning error temperature point combination under numerically-controlled machine thermal effect according to claim 1, it is characterized in that: the selection optimization method of lathe location error compensation modeling temperature point of the present invention, it is a kind of comprehensive selection method based on grey correlation analysis and rough set theory, realize according to following steps
First the correlative factor producing positioning error under thermal effect is considered, comprise the impact that the to-and-fro movement of machine tool motion part produces heat, motor running heating, each parts heat-generation and heat of lathe and environment temperature, analyze the position determining sensor in harvester bed tempertaure data experiment according to this; As shown in table 1,29 sensor positions refer to table 1, are numbered 1,2,3,4,6,8,14 and No. 18 sensor and are arranged in the exemplary position of front-end of spindle and rear end, each four of rear end, front end, and each transducer spacing is equal, is looped around on axle head; Sensor spacing is installed, and avoids the too near interference mutually of distance, not comprehensive apart from detection too far away, installs identical with lower sensor; 5,7,11 and No. 15 are arranged on spindle box body front and back end and upper end; 12,19,21,22,24,28 and No. 29 are arranged on X, Y, Z tri-axial filament thick stick motor, bearing, shaft coupling and nut; 20,23,24,26 and No. 27 are arranged on X, Y, Z axis direction guiding rail; 9,10,13,16 and No. 17 are arranged in vertical slide plate, worktable and environment temperature;
Table 1 29 sensor position tables
Laser interferometer is fixed on lathe: the receiver (4) of the generating laser (1) of laser interferometer, the main shaft (2) of lathe, worktable (3), laser interferometer; First generating laser (1) is arranged on the smooth place of worktable (3) front end, afterwards the receiver (4) of laser interferometer is arranged on the main shaft (2) of lathe; Adjust the laser head of the generating laser (1) of laser interferometer after installation, make the axis of measurement axis and machine tool movement or parallel point-blank, harmonize by light path straight; During standby bed operating, on request the correlation parameter of lathe is measured;
Then run lathe and carry out data acquisition; The data that recycling grey correlation analysis collects, filter out the sensor layout points that m related coefficient is large; Then with Rough Set Analysis software, temperature data and positioning error data are processed, yojan is carried out to temperature point, obtain the individual feasible temperature point combination of n; Finally, the comprehensive temperature point combination analyzing m temperature sensitive point and n, filters out and comprises the temperature point combination that sensitive temperature measuring point is maximum and the degree of association is the highest, is required Optimal Temperature measuring point combination.
3. a kind of selection optimization method about positioning error temperature point combination under numerically-controlled machine thermal effect according to claim 1, is characterized in that: step 1, gathers time dependent temperature variable and positioning error amount in numerically-controlled machine operational process:
First, in the critical positions of numerically-controlled machine, k temperature sensor is installed and carries out temperature survey, laser interferometer is fixed on lathe and carries out positioning error measurement;
Then, first measurement and positioning error under lathe cold conditions, after measurement, quick moving movement axle makes lathe temperature raise, and then measure, again temperature rise so repeat to tend towards stability to each temperature variation of lathe, namely lathe reaches thermal equilibrium state and terminates measurement; Can obtain by running lathe: the temperature that 1. temperature sensor of k position records measures T{T over time
1(t), T
2(t) ..., T
k(t) }; 2. lathe positioning error amount Y (t) that records of laser interferometer;
Step 2, application grey correlation analysis filters out m sensitive temperature point position:
Grey System Analysis be according to characteristic parameter series each in system between the systematic analysis carried out of similar close degree mathematical theory;
In processing cutting process, lathe positioning error is obvious in the discontinuous point place change that lathe runs, selecting machine tool carrys out modeling analysis at the detected value of the material time Nodes of start, shutdown, also contemplates the even time interval of relational appraise to data acquisition simultaneously; Specifically, with certain node access time unit interval, l group data can be got;
Due to implication and the object difference of each influence factor, thus desired value has different dimensions and data level usually, if the data between two sequences differ greatly in size, then the effect of fractional value sequence is easily covered by large sequence of values, for the ease of comparing, ensure that there is between each factor equivalence and same sequence, need process raw data, make it nondimensionalization and normalization;
If reference sequence be positioning error data Y (t)=Y (j) | j=1,2 ..., l}, comparand is classified as k temperature point data T
i={ T
i(j) | i=1,2 ..., k; J=1,2 ..., l}; Then Y (t) is to T
icorrelation coefficient at jth point:
In formula, Δ
0ij () is jth point Y (t) and T
ithe absolute value of (t), Δ
0i(j)=| Y (t)-T
i(t) |; min
imin
jΔ
0ij () is the two poles of the earth lowest difference; max
imax
jΔ
0ij () is the maximum difference in the two poles of the earth; ρ is resolution ratio, and ρ ∈ [0,1], generally gets ρ=0.5, in concrete operation, according to the degree of association between each data sequence, can adjust ρ value, to increase the resolution characteristic of comparative analysis;
Degree of association γ between two sequences
0ithe degree of association coefficient ξ in available two each moment of sequence
0ij the mean value of () calculates, that is,
In formula, it is the degree of association of subsequence i and auxiliary sequence; L is the data amount check of two comparative sequences;
Finally by the degree of association γ of each subsequence to same auxiliary sequence
0iby size order line up, namely form inteerelated order, it directly reflects each subsequence " primary and secondary " relation to same auxiliary sequence, namely represent these point position temperature variation on lathe produce positioning error affect size; Now, a threshold value is set
as correlation coefficient value γ
0kbe greater than γ ' time, temperature point position is retained, and all the other temperature point positions are then cast out, by k temperature point be successfully reduced to m responsive measuring point T ' T '
1(t), T '
2(t) ..., T '
m(t) };
Establish a grey relational order by above-mentioned analytical calculation, γ is got to inteerelated order
0kbe greater than the factor of γ ', then have T
1> T
6> T
8> T
10> T
13> T
5> T
14> T
18> T
11> T
19; This grey relational order represents the arranging situation to the temperature point that positioning error has the greatest impact;
Step 3, according to the principle of rough set theory, carries out pre-service to positioning error under lathe thermal effect and temperature data, forms a decision table:
Using the temperature of surveyed a k position as conditional attribute C, i.e. C={T
1(t), T
2(t) ..., T
k(t) }, the positioning error displacement of surveying attribute D, i.e. D={Y (t) as a result }, thus establish a system decision-making table K=(U, C ∪ D), and this decision table is established as an Excel table;
Step 4, utilizes Rough Set Analysis software to draw the individual feasible temperature point combination of n:
By the system decision-making table K=(U set up above, C ∪ D) Excel table be input in Rough Set Analysis software (ROSETTA) and go, by carrying out Data Reduction process after Data-parallel language, Data Discretization, obtain the temperature point combination that n kind is feasible, the combination of these temperature points can than more completely expressing machine tool temperature field distribution situation;
Following feasible combination can be obtained through Rough Set Analysis software analysis:
{ T
1t
5t
6t
8t
10t
13t
14, { T
1t
6t
8t
10t
13t
14t
18, { T
5t
6t
8t
10t
13t
14t
18, { T
1t
5t
6t
8t
10t
11t
19, { T
1t
5t
6t
8t
10t
13t
18, { T
1t
5t
6t
8t
10t
13t
14t
18; These six kinds of combinations can than more completely reacting whole numerically-controlled machine thermo parameters method situation and affecting situation to positioning error;
Step 5, comprehensive identifier bed Optimal Temperature measuring point of analyzing combines, and completes selection optimization method:
M sensitive temperature measuring point of Integrated comparative yojan and n temperature point combination, filter out and comprise the temperature point combination that sensitive temperature measuring point is maximum and the degree of association is the highest, is required Optimal Temperature measuring point combination;
By comparing grey relational order and temperature point combination, an Optimal Temperature measuring point combination can be drawn: { T
1, T
5, T
6, T
8, T
10, T
13, T
14;
After above-mentioned 5 steps complete, an optimum point position combination can be obtained, reach cost-saving, simplify the operation of heat error compensation experiments of measuring and improve the object of robustness of Model of locating error.
4. a kind of selection optimization method about positioning error temperature point combination under numerically-controlled machine thermal effect according to claim 1, it is characterized in that: in described step 2, usually just value conversion, equalization conversion and extreme difference can be adopted to convert three kinds of disposal routes to raw data, choose transform method according to corresponding requirements.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN105666244A (en) * | 2016-01-06 | 2016-06-15 | 北京工业大学 | Method for reducing number of boring bar thermal elongation error temperature measurement points of numerical-control boring machine under thermal effect |
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| CN113238480B (en) * | 2021-05-17 | 2022-04-26 | 合肥工业大学 | Parameterized regulating and controlling system and method for metal cutting machining cooling gas jet |
| CN116437649A (en) * | 2023-06-13 | 2023-07-14 | 浙江德塔森特数据技术有限公司 | Machine room safety operation and maintenance method and device based on blockchain and readable storage medium |
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| CN117170308A (en) * | 2023-11-02 | 2023-12-05 | 中国机械总院集团云南分院有限公司 | Machine tool dynamic error compensation method and system based on instruction sequence analysis |
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