CN103971025B - A kind of fault of numerical control machine tool correlationship Dynamic Variation Analysis method - Google Patents

A kind of fault of numerical control machine tool correlationship Dynamic Variation Analysis method Download PDF

Info

Publication number
CN103971025B
CN103971025B CN201410230927.4A CN201410230927A CN103971025B CN 103971025 B CN103971025 B CN 103971025B CN 201410230927 A CN201410230927 A CN 201410230927A CN 103971025 B CN103971025 B CN 103971025B
Authority
CN
China
Prior art keywords
fault
subsystems
subsystem
correlation
rate
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Expired - Fee Related
Application number
CN201410230927.4A
Other languages
Chinese (zh)
Other versions
CN103971025A (en
Inventor
王晓燕
张英芝
申桂香
孙曙光
谷东伟
尹志勇
赵佳
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Jilin University
Original Assignee
Jilin University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Jilin University filed Critical Jilin University
Priority to CN201410230927.4A priority Critical patent/CN103971025B/en
Publication of CN103971025A publication Critical patent/CN103971025A/en
Application granted granted Critical
Publication of CN103971025B publication Critical patent/CN103971025B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Landscapes

  • Testing And Monitoring For Control Systems (AREA)

Abstract

The invention discloses a kind of fault of numerical control machine tool correlationship Dynamic Variation Analysis method; Being intended to overcome prior art can not determine in the fault chain mutually disturbing fault (I.F), the problem of the degree of correlation between the multisystem that there is complicated correlationship, step is: step 1: utilize FMECA analytical technology to fault data process, carry out the division of the trouble location of each subsystem of lathe, arrange the data between subsystems with dependent failure; Step 2: analyze related data, the interaction type between summary and induction correlation subsystem, the kind of failure definition chain and fault chain key element; Step 3: for different dependent failure chains, utilize the dependence relation of independent failure rate, dependent failure rate and resultant fault rate, try to achieve the resultant fault rate of dependent failure subsystem, set up the Calculation of correlation factor model of all fault chains respectively, the related coefficient model system of composition dependent failure; Step 4: the analysis considering the maintenance policy of dependent failure.

Description

Dynamic change analysis method for numerical control machine tool fault correlation relationship
Technical Field
The invention belongs to the technical field of numerical control machines, relates to a numerical control machine related fault analysis method, and particularly relates to a numerical control machine fault related relation dynamic change analysis method.
Background
The existence of related faults of the numerical control equipment causes the change of the inherent fault rate of the numerical control equipment, and if the fault correlation between subsystems is neglected in the reliability design and distribution stage, the design value of the reliability inevitably generates a large error with the actual production occurrence value. Meanwhile, if the existence of the related faults is used for predicting maintenance with the reliability of the independent faults, the maintenance time node is delayed. There are 4 most typical related faults among system faults: series faults, negative correlation faults, common cause failures, and mutual interference faults. The invention relates to a mutual interference fault type (I.F for short), and the common characteristics of the related faults are as follows: component a can accelerate or lead to failure of component B when it fails, sometimes with such destructive effects interacting. The result of this interaction is an increase in the failure rate of the failed system, the magnitude of the increase being related to the degree of interaction between the subsystems. The related faults can be caused by improper design, machining, manufacturing, installation and operation of the machine tool, so that the occurrence probability is high and the hazard is strong. With the concern of scholars at home and abroad on related faults in recent years, related researches are deepened continuously, but the related researches on the type of mutual interference faults among subsystems which are commonly existing on the numerical control machine tool are not reported.
The degree of mutual interference between subsystems is defined as the correlation coefficient. The literature devoted to the research of the degree of the correlation is few, and the only literature is to roughly estimate other reliability indexes as parameters in order to realize the reliability indexes, and the importance and the rigor of the reliability indexes in the reliability calculation are ignored. Although the existing analysis method and model realize the determination of the correlation coefficient to a certain extent, both have certain theoretical limitations. The main analytical methods are as follows: 1. the mathematical statistics method uses the incidence of related faults as related coefficients, so that the change of the related coefficients is determined by the number of the collected samples, and the error is large; 2. and the test method is used for obtaining a large amount of test data by using a test means to determine the correlation coefficient model. The method has strong pertinence, high implementation cost and no general popularization; 3. in the subjective evaluation method, an experienced expert scores the degree of correlation between related systems, and calculates a comprehensive score value as a correlation coefficient. The method has strong subjectivity and large assignment error; and 4, a Copula function method, wherein the Copula function describes the correlation among variables, the function for connecting the variable joint cumulative distribution function and the variable edge cumulative distribution function can be used for calculating the correlation coefficient among the subsystems by using the related fault data of the subsystems, and the correlation coefficient is common and unique. The method is complex in calculation, and interaction relation and action direction between subsystems cannot be clarified, so that analysis of complicated correlation relation between multiple systems and model establishment of multiple correlation coefficients cannot be realized by a model; 5. the method is only suitable for the multi-mode correlation of parts per se, and is difficult to realize the calculation of the correlation coefficient among the multiple systems because the correlation relation of the function functions of the main fault modes among the multiple systems cannot be determined; 6. the failure rate method is used for establishing a relationship of failure rates among related subsystems, deriving a correlation coefficient and determining the correlation degree of the subsystems. But the research of the existing failure rate method is terminated by the calculation of the correlation coefficient between the two subsystems.
In the analysis method for the correlation degree among all the related subsystems, the fault rate method utilizes the variation relation between the independent fault rate and the related fault rate to reflect the correlation degree more accurately, because the method has a quantification result and can also clarify the interaction direction among the subsystems. However, the existing analysis process has theoretical limitation, the analysis method can only determine the degree of correlation between two related subsystems, and under the condition of a plurality of complex system correlation relations, as the correlation relation existing in each subsystem is not limited to one, fault data of the same subsystem may be from different related subsystems, thereby causing difficulty in further analysis.
Disclosure of Invention
The invention aims to solve the problem that the prior art cannot determine the correlation degree between multiple systems with complicated correlation in a fault chain of a mutual interference fault (I.F), and provides a method for analyzing the dynamic change of the fault correlation of a numerical control machine tool.
In order to achieve the above object, the present invention provides a method for analyzing dynamic changes of a numerical control machine tool fault correlation relationship, including the following steps:
step 1: and processing the fault data by using an FMECA analysis method, performing statistical analysis on the fault data of each subsystem of the machine tool, and sorting the data with related faults among the subsystems.
Step 2: and analyzing the related fault data, summarizing and summarizing the action form of the fault type of the mutual interference fault I.F among the related subsystems, and defining the type of the fault chain and the fault chain element.
And step 3: and (3) for different related fault chains, respectively deducing correlation coefficient calculation models of all fault chains by utilizing the independent fault rate, the dependent relation of the related fault rate and the comprehensive fault rate and utilizing the comprehensive fault rate model of the related fault subsystem, wherein the correlation coefficient models of all fault chains form a correlation coefficient model system of the related fault.
And 4, step 4: analysis of the repair strategy taking into account the associated fault.
The types of the fault chain in the technical scheme include five types:
the first method comprises the following steps: the fault chain has only two sub-chainsSystem, and acting unidirectionally, as a subsystem during operation of the machine toolCan affect the subsystemUp to the subsystemIn case of failure, the subsystemSubsystem pairNo influence is generated;
and the second method comprises the following steps: the fault chain is only provided with two subsystems, the two subsystems interact with each other, the bad motion states of the two subsystems are mutually influenced to form a vicious circle until one system stops running due to the fault;
and the third is that: the fault chain is composed of a plurality of subsystems, and the subsystemsThe motion state of the system simultaneously affects a plurality of subsystems and is not affected by other related subsystems;
and fourthly: the fault chain is composed of a plurality of subsystems, and the subsystemsAffected by multiple subsystems without any relevant effect on any other subsystem;
and a fifth mode: the fault chain is composed of more than three subsystems, is a combination form of part or all of the four basic fault chains, at least one subsystem is subjected to the correlation action of more than two subsystems, and has a fault intermediate point subsystem, and complicated correlation relations are formed among the related subsystems and belong to the type of the complicated related fault chain.
The definition of the fault chain elements in the technical scheme refers to the definition of the fault subsystem according to the position and the action of the fault subsystem in the fault chain in the fault occurrence process; the fault chain elements include:
(1) starting point of related fault:
in a fault chain with correlation, a subsystem which only affects other subsystems but is not affected by other subsystems is called a correlation fault starting point;
(2) end of related failure:
in a fault chain with a correlation relationship, a subsystem which is only influenced by other subsystems and does not influence the other subsystems is called a correlation fault terminal;
(3) the fault intermediate point:
in a fault chain with a correlation relationship, a subsystem with the influence and affected relationship is called a fault intermediate point.
In the technical scheme, for different related fault chains, a correlation coefficient calculation model of all fault chains is respectively deduced by using the independent fault rate, the dependent relation of the related fault rate and the comprehensive fault rate and using a comprehensive fault rate model of a related fault subsystem, specifically according to the comprehensive fault rate calculation model:
(1)
: for the subsystem in the case of a relevant faultThe comprehensive fault rate is obtained by calculating fault data in production;
: as subsystems ofThe independent failure rate is determined by inherent reliability, and the product is obtained through test or production data before leaving factory and is in a subsystemWithout being affected by the associated fault, theoretically
: as subsystems ofReceptor systemThe correlation coefficient of the effect is such that,when is coming into contact withTime, without correlation, i.e. subsystemsWill not cause failureIn case of failure whenTime, fully correlated, i.e. sub-systemThe occurrence of a fault necessarily causesA failure occurs;
: to a subsystemSubsystems for producing a correlationThe associated failure rate of (c);
and respectively establishing correlation coefficient calculation models of all fault chains according to the comprehensive fault rate model and the formula (1) and aiming at the characteristics of the fault chains, wherein the correlation coefficient calculation models of all fault chains form a correlation coefficient model system of the relevant fault.
In the technical scheme, for the first and third types of the fault chains, the correlation relationship of the fault chains is one-way correlation, and the correlation fault terminal subsystemSubject to only one subsystemIs affected by the fault, then the subsystem in question is faultyThe overall failure rate of (2) is obtained from equation (1):
(2)
then there are:
      (3)
due to the relevant subsystemsIs the starting point of the related fault and is not related to other subsystems, so(ii) a Wherein:
: as subsystems ofThe independent failure rate of;
: for the subsystem in the case of a relevant faultThe overall failure rate of;
: as subsystems ofReceptor systemCorrelation coefficient of action.
In the fourth aspect of the technical solution, the correlation of the fault chain is a multi-system one-way correlation, and the correlation fault end pointAre simultaneously affected by the correlation of a plurality of subsystems, andfor the end of a related fault, related fault endThe running state does not affect other related subsystems; sub-systemIntegrated failure rate ofByDetermination of correlation relationship as a computing subsystemReceptor systemCorrelation coefficient of actionValues, make the following assumptions:
(1) sub-systemAndsub-system dependent correlation coefficientThere is no linear correlation between them,(ii) a Order toThen, the following equations (2) and (3) hold, and the following equation (4) is derived from the equation (2):
(4)
as subsystems ofIs subjected toSub-failure rates of subsystem-related actions; by subsystemFault data removal ofOther subsystems than the one in which the fault data is relevant are modeled.
(2) Sub-systemTo receiveSub-failure rate of related actions of subsystemsAnd subsystemComprehensive failure rateIn a functional relationship:
(5)
sub-systemAll are related fault starting points and are used for the subsystemIs equal to the subsystemThe independent failure rate of; in formula (4),,WherebyAccording to the formulas (1) and (4), the formula (5) is derived as the formula (6):
(6)
: as subsystems ofReceptor systemCorrelation coefficient of action.
In the technical scheme, for the second and fifth types of the fault chains, the correlation relationship of the fault chains is multi-system correlation, and when the comprehensive fault rate of each subsystem is calculated, the correlation between the subsystem and other related subsystems needs to be respectively solvedBarrier rate and correlation coefficient; the names of the system are respectively: starting point of related faultEnd of related failureIntermediate point of correlation failureThen the related fault end pointThe comprehensive failure rate model of (2) is as follows:
(7)
obtaining the subsystem from equation (4)The failure rate model of (1) is as follows:
(8)
: is a receptor systemInfluencing subsystemThe associated failure rate of (c);
: is a receptor systemInfluencing subsystemThe associated failure rate of (c);
: to a subsystemSubsystems for producing a correlationThe associated failure rate of (c);
: to a subsystemSubsystems for producing a correlationThe associated failure rate of (c);
as subsystems ofReceptor systemCorrelation coefficient of action;
as subsystems ofReceptor systemCorrelation coefficient of action;
calculating the failure rate of each component;is the starting point of the related fault, thereforeThen, thenCan be obtained.
The subsystem in the technical schemeSubsystems for producing a correlationAssociated failure rate ofThe value analysis process of (a) is as follows, with the subsystemIs a subject of studySystemAs fault intermediate point, subsystemWhile being influenced by the subsystemIs the subsystemThe comprehensive failure rate model is as follows:
(9)
: as subsystems ofThe overall failure rate of;
: as subsystems ofThe independent failure rate of;
: as subsystems ofReceptor systemCorrelation coefficient of action;
: to a subsystemSubsystems for producing a correlationThe associated failure rate of (c);
due to the fact thatIs a starting point of the related fault, soByThe production failure data of (a) is obtained,as subsystems ofIs known to be capable of independent failure rates,as determined by equation (9); according toAndwhether the information is related or not is judged,as subsystems ofReceptor systemThe correlation coefficient of the effect is such that,the value is taken in two cases,
the first method comprises the following steps:andis irrelevant
And the second method comprises the following steps:andcorrelation
The value is determined,the calculation is performed according to equation (8).
In the technical scheme, the analysis of the maintenance strategy considering the related faults specifically comprises the steps of revising the reliability of the subsystems by utilizing a determined correlation coefficient model system among the subsystems and calculating and predicting maintenance nodes;
the maintenance strategy of the system is formulated and optimized according to the reliability, and when the reliability of the system or the subsystem is less than a scheduled threshold value, preventive maintenance is required to be carried out on the system or the subsystem; if subsystemThe reliability is as follows if there is no related fault:
(11)
: as subsystems ofOnly the reliability model under the condition of independent failure rate;
consider a subsystem with an associated faultThe reliability model of (2) is:
 (12)
therefore, the method comprises the following steps:
(13)
: to the sub-systemEstablishing a reliability model of the comprehensive failure rate;
the reliability calculated by the independent failure rate has a large possibility when the subsystemWhen the reliability of (2) reaches a prescribed threshold value, the subsystemWhen the time point calculated by the reliability model of (1) is used as the maintenance node, since the time node calculated by the independent failure rate is larger than the time node calculated by the related failure rate, the subsystem calculated by the equation (11)The maintenance time node of (a) is taken as the basis of the maintenance plan, and the backward delay of the preventive maintenance plan is inevitably caused.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the dynamic change analysis method for the related relation of the faults of the numerical control machine tool, provided by the invention, a large amount of fault data are considered as a basis, the data change rule of the related faults of I.F is explored, the related relation form among subsystems is used as a basis to carry out fault chain type division on I.F fault types, and an important analysis basis is provided for the analysis of the related faults.
2. The method for analyzing the dynamic change of the related relation of the faults of the numerical control machine tool takes a fault rate method as an analysis means, takes the independent fault rate, the related fault rate and the dependent relation among the comprehensive fault rates as the basis, determines the related coefficient models among the subsystems according to the characteristics of different I.F related fault chains, forms a related coefficient model system, and establishes the analysis method of the related relation and the related degree among complex multiple systems.
3. The method for analyzing the dynamic change of the numerical control machine tool fault correlation breaks through the theoretical limitation of the prior art and expands a correlation fault theoretical system. The analysis method provided by the invention is used for optimizing and predicting the maintenance plan, so that the accuracy of maintenance nodes is improved, the failure rate of equipment is reduced, and a method and a theoretical basis are provided for the reliability increase of the equipment.
Drawings
Fig. 1 is a flow chart of a method for analyzing dynamic changes of a numerical control machine tool fault correlation according to the present invention;
fig. 2 is a schematic diagram of the unidirectional functions of the first fault chain, i.e., two subsystems, of the five fault chains in the method for analyzing dynamic changes of fault correlation of a numerical control machine tool according to the present invention;
fig. 3 is a schematic diagram of interaction between two subsystems, which is a second fault chain of the five fault chains in the method for analyzing dynamic changes of fault correlation of a numerical control machine tool according to the present invention;
fig. 4 is a schematic diagram of a third fault chain, i.e., a single subsystem, of the five fault chains in the method for analyzing dynamic changes of fault correlation of a numerical control machine tool according to the present invention acting on multiple subsystems simultaneously;
fig. 5 is a schematic diagram of a fourth fault chain, namely a single subsystem, of the five fault chains in the method for analyzing dynamic changes of fault correlation of a numerical control machine tool according to the present invention, where the fourth fault chain is simultaneously affected by multiple subsystems;
fig. 6 is a schematic diagram of a fifth fault chain, i.e. a complex correlation, of the five fault chains in the method for analyzing dynamic changes of fault correlation of a numerical control machine tool according to the present invention;
fig. 7 is a relational diagram of a servo system, a hydraulic system and a tool rest system in a method for analyzing dynamic changes of related relations of faults of a numerical control machine tool.
Detailed Description
The following describes a method for analyzing dynamic changes of a numerical control machine tool fault correlation in detail with reference to the accompanying drawings:
the method for analyzing the dynamic change of the numerical control machine tool fault correlation takes a large amount of investigation fault data as a basis, finds out the rule of data change of the correlation fault, classifies fault chains for interaction forms among subsystems, finds out the dependency relationship among independent fault rates, correlation fault rates and comprehensive fault rates according to different fault chains, determines a correlation coefficient model among the subsystems, establishes an analysis method of the correlation relationship and the correlation degree among complex multiple systems by taking a fault rate method as an analysis basis, breaks through the theoretical limitation of the existing method, and optimizes, predicts, maintains and plans by the analysis method.
A method for analyzing dynamic changes of numerical control machine tool fault correlation comprises the following steps:
step 1, processing fault data by using an FMECA analysis technology, performing statistical analysis on the fault data of all subsystems of the machine tool, and sorting the data with related faults among all the subsystems.
1) And dividing the fault according to the characteristics of the fault mode, the fault occurrence position and the fault occurrence reason, and determining the fault occurrence frequency of the subsystem and the severity and the hazard of the fault mode.
2) And calculating the fault interval time of the whole computer and the fault interval time of each subsystem.
3) And screening fault data with correlation, and determining an interaction form among subsystems.
And 2, analyzing related fault data, summarizing and summarizing interaction forms of mutual interference faults (I.F) among related subsystems, and defining the types and elements of fault chains:
1) defining the kind of fault chain:
referring to fig. 2, fig. 3, fig. 4, fig. 5 and fig. 6, the complicated correlation among a plurality of subsystems of the numerical control machine tool is simplified, the complicated surface phenomenon is uncovered, and five basic forms of mutual interference faults are summarized. Suppose a numerically controlled machine tool is composed ofA subsystem component, respectivelyAny one of the complex correlation fault relations can be formed by the five fault chains or several fault chains.
Referring to fig. 2, the first: the fault chain has only two subsystems and has a unidirectional function, namely a subsystem during the operation of the machine toolCan affect the subsystemUp toIn case of failure, the subsystemSubsystem pairNo influence is generated;
referring to fig. 3, the second: the fault chain is only provided with two subsystems, the two subsystems interact with each other, the bad motion states of the two subsystems are mutually influenced to form a vicious circle until one system stops running due to the fault;
referring to fig. 4, third: the fault chain is composed of a plurality of subsystems, and the subsystemsThe motion state of the system simultaneously affects a plurality of subsystems and is not affected by other related subsystems;
referring to fig. 5, fourth: the fault chain is composed of a plurality of subsystems, and the subsystemsAffected by multiple subsystems without any associated fault effects on any other system;
referring to fig. 6, the fifth: the fault chain is composed of three or more subsystems, is the simplest combination form of the four basic fault chains, and belongs to the type of a complex correlation relation fault chain.
2) Defining fault chain elements:
the faulty subsystem is defined according to its location and role in the fault chain during the fault occurrence. The present invention is defined as follows:
1. starting point of related fault:
in the fault chain of the correlation, the subsystem which only affects other systems and is not affected by other systems is called the correlation fault starting point, as shown in fig. 2, 4, 5 and 6
2. End of related failure:
in the fault chain of the correlation, the subsystem which is only affected by other subsystems and does not affect other subsystems is called the correlated fault end point, as shown in fig. 2, 4, 5 and 6
3. Intermediate point of correlation failure
In the fault chain of the correlation, the subsystem with the influence and influenced relation being simultaneously existed is called as the correlation fault intermediate point, as shown in FIG. 4In FIG. 3
And 3, aiming at different related fault chain characteristics, establishing a model system of a related coefficient by utilizing the dependence relationship of the independent fault rate, the related fault rate and the comprehensive fault rate:
1) and aiming at different characteristics of the related fault chains, establishing a model system of the related coefficients by utilizing the independent fault rate, the related fault rate and the dependency relationship of the comprehensive fault rate. Specifically, a model is calculated according to the related fault rate:
(1)
: for the subsystem in the case of a relevant faultThe comprehensive fault rate is obtained by calculating fault data in production;
: as subsystems ofThe independent failure rate of the system is determined by inherent reliability, and is usually obtained by test or production data before the product leaves a factory and in a subsystemWithout being affected by the associated fault, theoretically
As subsystems ofReceptor systemThe correlation coefficient of the effect is such that,when is coming into contact withTime, without correlation, i.e. subsystemsWill not cause failureIn case of failure whenTime, fully correlated, i.e. sub-systemThe occurrence of a fault necessarily causesA failure occurs;
: to a subsystemSubsystems for producing a correlationThe associated failure rate of (2).
2) And aiming at different characteristics of the related fault chains, establishing a model system of the related coefficients by utilizing the independent fault rate, the related fault rate and the dependency relationship of the comprehensive fault rate. Specifically, according to the formula (1), for the characteristics of five fault chains, correlation coefficient calculation models of all fault chains are respectively established, and a correlation coefficient model system of the relevant fault is formed as follows:
1. correlation of fault chainsFor simple one-way correlation, i.e. first and third of the fault chain (see fig. 2, 4), the correlated fault termination subsystemSubject to only one subsystemIs then associated with the fault destination subsystemThe overall failure rate of (2) is obtained from equation (1):
(2)
the correlation coefficient calculation model is:
(3)
due to the relevant subsystemsIs the starting point of the related fault and is not related to other subsystems, so,As subsystems ofIndependent failure rate of.As subsystems ofReceptor systemCorrelation coefficient of action;
2. the correlation relationship of the fault chain is multi-system one-way correlation, namely the fourth kind of fault chain, referring to fig. 5, the correlated fault end pointAre simultaneously affected by the correlation of a plurality of subsystems, andfor the end of a related fault, related fault endThe operating state does not affect other related subsystems. Comprehensive failure rateByThe correlation is determined as shown in equation (1). For computing subsystemsReceptor systemCorrelation coefficient of actionThe value satisfies the following two assumptions (1) and (2):
(1) sub-systemAndsub-system dependent correlation coefficientThere is no linear correlation between them,. Instant gameWhen the equations (2) and (3) are satisfied, the correlation diagram of FIG. 4 can be decomposed intoThe formula (4) is derived from the formula (2) as the relation expressed in fig. 1.
(4)
As subsystems ofIs subjected toFailure rate of subsystem-related actions, slave subsystem based on assumption (1)In the fault data eliminating subsystemOther subsystems of interest than the subsystems of interestAnd modeling the related fault data to obtain the fault data.
(2) Sub-systemTo receiveSub-failure rate of related actions of subsystemsAnd subsystemComprehensive failure rateIs in a functional relationship.
(5)
Taking the relational form of FIG. 4 as an example, the subsystemsAll are related fault starting points and are used for the subsystemIs equal to the subsystemIndependent failure rate. In formula (4),,WherebyAccording to the formulas (1) and (4), the formula (5) is derived as the formula (6):
(6)
3. the correlation relationship of the fault chain is a multi-system complex correlation, namely, a fifth fault chain and a second fault chain, as shown in fig. 3 and 6 (fig. 3 can be regarded as a special case of fig. 6,andall considered as fault intermediate points), each subsystem in the graph has more than two correlations. When calculating the failure rate of each subsystem, the related failure rate and the related coefficient of the subsystem and other related subsystems need to be respectively calculated. With the subsystems in FIG. 6For example, the failure rate is calculated by setting the names of the subsystems as: starting point of related faultEnd of related failureCorrelation intermediate pointAccording to the formula (1) have
(7)
From equation (4)
(8)
: is a receptor systemInfluencing subsystemThe associated failure rate of (c);: is a receptor systemInfluencing subsystemThe associated failure rate of (c);: to a subsystemSubsystems for producing a correlationThe associated failure rate of (c);: to a subsystemSubsystems for producing a correlationThe associated failure rate of (c);is a subsystemReceptor systemCorrelation coefficient of action;: as subsystems ofReceptor systemCorrelation coefficient of action.
Calculate the score as described in equation (4)Calculating a fault rate; in formula (8)Is the starting point of the related fault, thereforeThen, thenCan be solved;is relatively complex because of the subsystemAs a fault intermediate point, pairIs also influenced byThe analysis process of the value of (A) is as follows, firstlyFor the object of study, the subsystemThe comprehensive failure rate of (2) is:
(9)
: sub-systemThe overall failure rate of;: sub-systemThe independent failure rate of;as subsystems ofReceptor systemCorrelation coefficient of action:: to a subsystemSubsystems for producing a correlationThe associated failure rate of (2).
Due to the fact thatIs a starting point of the related fault, soByThe production failure data of (a) is obtained,as subsystems ofIs known to be capable of independent failure rates,can be determined by equation (9). According toAndwhether the information is related or not is judged,the value is divided into two cases
Andis irrelevant
Andcorrelation (10)
The value is determined,the calculation is performed according to equation (8).
To this end, a correlation coefficient calculation model architecture between multiple subsystems for I.F fault types of complex systems has been established. The correlation coefficient being timeFunction of (2), the associated fault causing the subsystemAfter a fault, the interaction is stopped, the numerical control equipment continues to operate after the fault is repaired, the related action is restarted, and the process is repeated repeatedly, so that the related relation is maintained during each fault interval, and if and only ifThe correlation coefficient is constant. Wherein,: to the sub-systemAnd (3) establishing a reliability model of the comprehensive failure rate.
Step 4. analysis of maintenance strategy taking into account relevant faults
1) And analyzing the maintenance strategy considering the related faults, specifically revising the reliability of the subsystems by using the determined correlation coefficient between the subsystems, and calculating the predicted maintenance node.
The maintenance strategy of the system is based on the reliabilityAnd optimizing, when the reliability of the system or the subsystem is less than the scheduled threshold value, preventive maintenance is needed to be carried out on the system or the subsystem. If subsystemIf the fault is an independent fault, the reliability model is as follows:
(11)
: as subsystems ofOnly the reliability model under the condition of independent failure rate;
the inevitable existence of related faults in actual production causes larger deviation of reliability calculation, and the deviation is more obvious particularly when the reliability of the whole machine is calculated, for example I.F related faults researched by the invention, the reliability of independent fault calculation tends to be larger, and subsystems with related faults are consideredThe reliability model of (2) is:
(12)
: to the sub-systemEstablishing a reliability model of the comprehensive failure rate;
therefore, the method comprises the following steps:
since the reliability value calculated with the individual fault is greater than the reliability value considering the associated fault, equation (11) results in a preventive maintenance schedule.
The method of the invention induces the fault chain type of the mutual interference fault model according to the action form of the relevant fault through the analysis of a large amount of numerical control machine fault data, establishes the relevant fault rate model according to the independent fault rate in the relevant fault, the dependent relation of the relevant fault rate and the comprehensive fault rate, and then establishes a correlation coefficient solving model system among the relevant subsystems according to the characteristics of each fault chain, thereby realizing the analysis method for determining the correlation action degree among the relevant subsystems of the numerical control machine, and providing a basis for the prediction maintenance plan of the system or the subsystem considering the relevant fault.
Example (b):
the invention takes the analysis of the complex correlation among three subsystems of the numerical control machine as an example.
Step 1: and processing the fault data by using an FMECA analysis technology, dividing fault parts of each subsystem of the machine tool, and sorting the data with related faults.
The data is derived from 13 month production fault tracking records of 175 machines of a certain model. After fault data is processed by FMECA analysis, the subsystems with correlation are found, and the correlation shown in fig. 7 is taken as an example.
And obtaining fault time points and related fault time points of each subsystem after processing by an FMECA (frequency modulated fluid dynamics) method, calculating a fault interval time value from the fault time points to be used as fault data, wherein the daily working system of the machine tool is a two-shift system, and a table 1 is a data processing result of the tool rest system. The calculation formula is as follows:
(13)
(14)
: first, theThe fault interval time is related in category, and the fault interval end point is related fault time point, such as 28.60 of fault data of the tool rest system in Table 1*: first, theA time point of occurrence of each fault, and the fault is a related fault;: same subsystem of same machine toolA failure time point immediately preceding the failure time point;: identity of the same machine toolSub-systemThe next fault interval time immediately adjacent;same subsystem of same machine toolThe fault time point is immediately following the fault time point.
TABLE 1 Fault data processing of tool holder systems
And (3) processing data of the servo system and the hydraulic system, such as the data processing process of the tool rest system, wherein the processed fault interval time values are shown in a table 2.
TABLE 2 subsystem Fault Interval time
The servo system in fig. 7 is the starting point of the related failure and is not affected by other systems. In the hydraulic system fault data in table 2, the data with the mark indicates that the fault interval time is caused by the relevant fault of the servo system; data with a mark in fault data of the tool rest system indicates that the fault interval time is caused by related faults of the hydraulic system; the data with "#" indicates that this fault interval time is due to a servo-related fault.
Step 2: and (3) judging the type of the fault chain according to the interaction form among the subsystems:
according to the complex correlation relationship of the three subsystems shown in fig. 7, the fault chain belongs to a fifth fault chain, and is the simplest complex correlation form, and the correlation coefficient value is determined by modeling according to formulas (7) to (10).
And step 3: and (3) analyzing and solving the related fault chain type determined in the step (2) by using a corresponding correlation coefficient model.
1. And obtaining an independent fault rate model, a comprehensive fault rate model and a related fault rate model of the three subsystems according to the production fault data.
Each subsystem of the machine tool eliminates the interference of related fault factors, and the fault rate is the inherent independent fault rate under the normal production state.
Table 3 shows the independent failure rate functions of the three subsystems, and the reliability function conforms to the weibull distribution.
Watch (A)3Subsystem independent failure rate function
The comprehensive failure rate of the three subsystems is obtained by processing failure data collected in a production field, Weibull distribution is a hypothesis distribution model, and a D test method is adopted for carrying out distribution fitting test. The formula (18) - (20) is shown in Table 4.
Watch (A)4Subsystem synthetic fault rate function
In this case, a modeling calculation and deduction process for obtaining the correlation coefficient between the tool post system and the other two subsystems in the correlation relationship of the three subsystems in fig. 7 is taken as an example. Is provided withFor the associated failure rate of the tool-carrier system effected in relation to the servo system, by the knifeThe fault data of the rack system is obtained by calculation after the fault data of the hydraulic system on the relevant action of the rack system is removed, and the formula is (21);the fault rate is calculated by removing the fault data of the tool rest system related action of the servo system from the tool rest fault data, wherein the fault rate is related to the tool rest system related action of the hydraulic system, and the formula is shown as (22).
TABLE 5 tool holder System related failure Rate function
2. Correlation analysis of tool holder system:
determining the related subsystems of the tool holder system according to the related relation chart 7, and according to the formula (7), the comprehensive failure rate formula of the tool holder system is as follows: (23)
whereinThe relative failure rate of the servo system to the tool rest system;the related failure rate of the hydraulic system to the tool rest system. According to the formula (8), the formula (23) is decomposed into the fault rate models of the tool rest system respectively related to the servo system and the hydraulic system, as shown in the formula (24).
(24)
The fault correlation coefficient of the servo system to the tool rest system is as follows:
(25)
since the servo system is the starting point of the failure, the method
(26)
Substituting the fault rate models (15), (17), (21) into equation (25), if forSubstitution of expressionsIs/are as followsPoint estimation valueThen there is
The model of the hydraulic system to the relevant failure coefficient of the tool rest system is as follows:
obtained from the formula (23)
(27)
WhereinIn order to know the failure rate of the mobile terminal,to be determined. Further analysis shows that the related fault of the hydraulic system to the tool rest system is related to the fault chain of the servo system to the hydraulic system, namely the related coefficient of the servo system to the hydraulic systemAndin this regard, the failure rate of the hydraulic system affected by the servo system affects the change in the failure rate of the carriage system according to equation (10):
(28)
substituting the fault rate models (17), (19), (22) into equation (27), if substitutedIs/are as followsPoint estimation valueThen there is
3. Based on the correlation coefficients obtained above, the overall failure rate of the tool holder system according to equation (23) is:
and 4, step 4: analysis of the repair strategy taking into account the associated fault.
The predicted maintenance of the tool holder system by independent fault analysis according to equation (11) is as follows:when a threshold of reliability is given asWhen, the predicted maintenance time isHours; the predicted service time for the tool holder system considering the associated failure is as follows:when a threshold of reliability is given asWhen, the predicted maintenance time isHours; as can be seen from the analysis of the maintenance strategy considering the related faults, the maintenance time node delay of the related faults based on the independent reliability is ignored. Therefore, the machine tool subsystem or the part can not be maintained in time within the threshold range of the reliability reduction, so that the fault rate of the machine is increased, the reliability is reduced, and the formulation of the ordering batch and the ordering date of the accessories is influenced.

Claims (1)

1. A method for analyzing dynamic changes of numerical control machine tool fault correlation is characterized by comprising the following steps:
step 1: processing fault data by using an FMECA analysis method, performing statistical analysis on the fault data of each subsystem of the machine tool, and sorting the data with related faults among the subsystems;
step 2: analyzing related fault data, summarizing and summarizing the action form of the mutual interference fault I.F fault types among related subsystems, and defining the types and elements of fault chains;
and step 3: aiming at different related fault chains, respectively deducing correlation coefficient calculation models of all fault chains by utilizing the independent fault rate, the dependent relation of the related fault rate and the comprehensive fault rate and utilizing the comprehensive fault rate model of a related fault subsystem, wherein the correlation coefficient models of all fault chains form a correlation coefficient model system of the related fault;
and 4, step 4: analysis of a maintenance strategy that takes into account the associated fault;
the types of fault chains include five:
the first method comprises the following steps: the fault chain only has two subsystems, has a unidirectional function, and is a subsystem in the running process of the machine toolCan affect the subsystemUp to the subsystemIn case of failure, the subsystemSubsystem pairNo influence is generated;
and the second method comprises the following steps: the fault chain is only provided with two subsystems, the two subsystems interact with each other, the bad motion states of the two subsystems are mutually influenced to form a vicious circle until one system stops running due to the fault;
and the third is that: the fault chain is composed of a plurality of subsystems, and the subsystemsThe motion state of (2) simultaneously affects a plurality of subsystemsIs not influenced by other related subsystems;
and fourthly: the fault chain is composed of a plurality of subsystems, and the subsystemsAffected by multiple subsystems without any relevant effect on any other subsystem;
and a fifth mode: the fault chain is composed of more than three subsystems, is a combination form of part or all of the four basic fault chains, at least one subsystem is subjected to the correlation action of more than two subsystems, and has a fault intermediate point subsystem, and complicated correlation relations are formed among the related subsystems and belong to the type of the complicated related fault chain;
the definition of the fault chain elements refers to the definition of the fault subsystem according to the position and the action of the fault subsystem in the fault chain in the fault occurrence process; the fault chain elements include:
(1) starting point of related fault:
in a fault chain with correlation, a subsystem which only affects other subsystems but is not affected by other subsystems is called a correlation fault starting point;
(2) end of related failure:
in a fault chain with a correlation relationship, a subsystem which is only influenced by other subsystems and does not influence the other subsystems is called a correlation fault terminal;
(3) the fault intermediate point:
in a fault chain with a correlation relationship, a subsystem with the influence and influenced relationship is called as a fault intermediate point;
for different related fault chains, the correlation coefficient calculation models of all fault chains are respectively deduced by using the independent fault rate, the dependent relation of the related fault rate and the comprehensive fault rate and using the comprehensive fault rate model of the related fault subsystem, specifically according to the comprehensive fault rate calculation models:
(1)
: for the subsystem in the case of a relevant faultThe comprehensive fault rate is obtained by calculating fault data in production;
: as subsystems ofThe independent failure rate is determined by inherent reliability, and the product is obtained through test or production data before leaving factory and is in a subsystemWithout being affected by the associated fault, theoretically
: as subsystems ofReceptor systemThe correlation coefficient of the effect is such that,when is coming into contact withTime, without correlation, i.e. subsystemsWill not cause failureIn case of failure whenTime, fully correlated, i.e. sub-systemThe occurrence of a fault necessarily causesA failure occurs;
: to a subsystemSubsystems for producing a correlationThe associated failure rate of (c);
according to a formula (1), respectively establishing correlation coefficient calculation models of all fault chains aiming at the characteristics of the fault chains, wherein the correlation coefficient calculation models of all fault chains form a correlation coefficient model system of the relevant fault;
aiming at the first and the third types of the fault chains, the correlation relationship of the fault chains is one-way correlation, and the correlation fault terminal subsystemSubject to only one subsystemIs affected by the fault, then the subsystem in question is faultyThe overall failure rate of (2) is obtained from equation (1):
(2)
then there are:
(3)
due to the relevant subsystemsIs the starting point of the related fault and is not related to other subsystems, so(ii) a Wherein:: as subsystems ofThe independent failure rate of;
: for the subsystem in the case of a relevant faultThe overall failure rate of;
: as subsystems ofReceptor systemCorrelation coefficient of action;
aiming at the fourth type of the fault chain, the correlation of the fault chain is multi-system one-way correlation, and the correlation fault end pointAre simultaneously affected by the correlation of a plurality of subsystems, andfor the end of a related fault, related fault endThe running state does not affect other related subsystems; sub-systemIntegrated failure rate ofByDetermination of correlation as a calculatorSystem for controlling a power supplyReceptor systemCorrelation coefficient of actionValues, make the following assumptions:
(1) sub-systemAndsub-system dependent correlation coefficientThere is no linear correlation between them,(ii) a Order toThen, the following equations (2) and (3) hold, and the following equation (4) is derived from the equation (2):
(4)
as subsystems ofIs subjected toSub-failure rates of subsystem-related actions; by subsystemFault data removal ofModeling the relevant fault data of other subsystems except the subsystems;
(2) sub-systemTo receiveSub-failure rate of related actions of subsystemsAnd subsystemComprehensive failure rateIn a functional relationship:
(5)
sub-systemAll are related fault starting points and are used for the subsystemIs equal to the subsystemThe independent failure rate of; in formula (4),,WherebyAccording to the formulas (1) and (4), the formula (5) is derived as the formula (6):
(6)
: as subsystems ofReceptor systemCorrelation coefficient of action;
aiming at the second type and the fifth type of the fault chain, the correlation relationship of the fault chain is multi-system correlation, and when the comprehensive fault rate of each subsystem is calculated, the correlation fault rates and correlation coefficients of the subsystem and other related subsystems are required to be respectively solved; the names of the system are respectively: starting point of related faultEnd of related failureIntermediate point of correlation failureThen the related fault end pointThe comprehensive failure rate model of (2) is as follows:
(7)
obtaining the subsystem from equation (4)The failure rate model of (1) is as follows:
(8)
: is a receptor systemInfluencing subsystemThe associated failure rate of (c);
: is a receptor systemInfluencing subsystemThe associated failure rate of (c);
: to a subsystemSubsystems for producing a correlationThe associated failure rate of (c);
: to a subsystemSubsystems for producing a correlationThe associated failure rate of (c);
as subsystems ofReceptor systemCorrelation coefficient of action;
as subsystems ofReceptor systemCorrelation coefficient of action;
calculating the failure rate of the sub-system according to the formula (4); in formula (8)Is the starting point of the related fault, thereforeThen, thenCan be solved;
the pair subsystemSubsystems for producing a correlationOf related failure rateThe value analysis process is as follows, and the subsystem is usedFor the object of study, the subsystemAs fault intermediate point, subsystemWhile being influenced by the subsystemThe influence of (a):
(9)
: as subsystems ofThe overall failure rate of;
: as subsystems ofThe independent failure rate of;
: as subsystems ofReceptor systemCorrelation coefficient of action;
: to a subsystemSubsystems for producing a correlationThe associated failure rate of (c);
due to the fact thatIs a starting point of the related fault, soByThe production failure data of (a) is obtained,as subsystems ofIs known to be capable of independent failure rates,as determined by equation (9); according toAndwhether the information is related or not is judged,as subsystems ofReceptor systemThe correlation coefficient of the effect is such that,the value is taken in two cases,
the first method comprises the following steps:andis not related to
And the second method comprises the following steps:andcorrelation (10)
The value is determined,can be solved according to the formula (8);
analyzing the maintenance strategy considering the related faults, specifically revising the reliability of the subsystems by utilizing an established correlation coefficient model system among the subsystems, and calculating and predicting maintenance nodes;
the maintenance strategy of the system is formulated and optimized according to the reliability, and when the reliability of the system or the subsystem is less than a scheduled threshold value, preventive maintenance is required to be carried out on the system or the subsystem; if subsystemThe reliability is as follows if there is no related fault:
(11)
: as subsystems ofOnly the reliability model under the condition of independent failure rate;
consider a subsystem with an associated faultThe reliability model of (2) is:
(12)
comprises the following steps:
(13)
: to the sub-systemEstablishing a reliability model of the comprehensive failure rate;
the reliability calculated by the independent failure rate has a large possibility when the subsystemWhen the reliability of (2) reaches a prescribed threshold value, the subsystemWhen the time point calculated by the reliability model of (1) is used as the maintenance node, since the time node calculated by the independent failure rate is larger than the time node calculated by the related failure rate, the subsystem calculated by the equation (11)The maintenance time node of (a) is taken as the basis of the maintenance plan, and the backward delay of the preventive maintenance plan is inevitably caused.
CN201410230927.4A 2014-05-28 2014-05-28 A kind of fault of numerical control machine tool correlationship Dynamic Variation Analysis method Expired - Fee Related CN103971025B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201410230927.4A CN103971025B (en) 2014-05-28 2014-05-28 A kind of fault of numerical control machine tool correlationship Dynamic Variation Analysis method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201410230927.4A CN103971025B (en) 2014-05-28 2014-05-28 A kind of fault of numerical control machine tool correlationship Dynamic Variation Analysis method

Publications (2)

Publication Number Publication Date
CN103971025A CN103971025A (en) 2014-08-06
CN103971025B true CN103971025B (en) 2015-07-29

Family

ID=51240513

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201410230927.4A Expired - Fee Related CN103971025B (en) 2014-05-28 2014-05-28 A kind of fault of numerical control machine tool correlationship Dynamic Variation Analysis method

Country Status (1)

Country Link
CN (1) CN103971025B (en)

Families Citing this family (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104850904A (en) * 2015-05-12 2015-08-19 上海能策燃气轮机有限公司 Analysis method for optimizing gas turbine overhaul and maintenance scheme
CN105278460B (en) * 2015-08-03 2018-02-09 吉林大学 Numerically-controlled machine tool system assembly reliability evaluation method based on cascading failure analysis
CN105844050B (en) * 2016-04-12 2018-01-30 吉林大学 Numerically-controlled machine tool system unit replacement time series analysis method based on time correlation
CN106597992B (en) * 2017-01-19 2019-10-08 吉林大学 A kind of numerically-controlled machine tool component importance analysis
CN107704677A (en) * 2017-09-29 2018-02-16 电子科技大学 Consider the lifting decelerator dynamic reliability modeling method of failure correlation
CN108021753B (en) * 2017-12-06 2019-03-08 吉林大学 A method of considering the Cnc ReliabilityintelligeNetwork Network assessment of operating condition difference
CN110472196B (en) * 2019-08-19 2020-05-05 广东工业大学 Production line multi-state reliability analysis and evaluation method
CN110598292A (en) * 2019-09-02 2019-12-20 中车株洲电力机车有限公司 Method for predicting reliability of rail transit product
CN112233420B (en) * 2020-10-14 2023-12-15 腾讯科技(深圳)有限公司 Fault diagnosis method and device for intelligent traffic control system
CN116757648B (en) * 2023-08-18 2023-11-03 天津市职业大学 Production and manufacturing management system and method based on artificial intelligence

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100953548B1 (en) * 2007-10-09 2010-04-21 도시바삼성스토리지테크놀러지코리아 주식회사 Method for write strategy and optical recording/reproducing apparatus thereof
CN102179722A (en) * 2010-12-20 2011-09-14 西安瑞特快速制造工程研究有限公司 Estimation method for operational reliability of numerical control machine based on proportional hazards model
CN103631201B (en) * 2013-12-17 2015-08-19 吉林大学 A kind of numerically-controlled machine subsystem reliability Impact analysis method

Also Published As

Publication number Publication date
CN103971025A (en) 2014-08-06

Similar Documents

Publication Publication Date Title
CN103971025B (en) A kind of fault of numerical control machine tool correlationship Dynamic Variation Analysis method
CN101520652B (en) Method for evaluating service reliability of numerical control equipment
CN105844050B (en) Numerically-controlled machine tool system unit replacement time series analysis method based on time correlation
US7546177B2 (en) Automated state estimation system for cluster tools and a method of operating the same
CN113867299B (en) IPPS problem solving method under uncertain disturbance based on digital twin
CN108171142B (en) A kind of causal method of key variables in determining complex industrial process
US7050935B1 (en) Method for assessing the reliability of technical systems
CN108038599B (en) Preventive maintenance period multi-target control method based on detection intervals
CN102929148A (en) Multiple product production mode statistical process control method based on T-K control chart
WO2014117967A1 (en) Method and apparatus for deriving diagnostic data about a technical system
Li et al. Market demand oriented data-driven modeling for dynamic manufacturing system control
CN104573224B (en) A kind of complex electromechanical systems reliability estimation method based on model inspection technology
CN102074957A (en) Primary frequency regulation and automatic generation control (AGC) load regulation coordinated control method
CN112668862A (en) Adaptability quantitative evaluation method of production line
CN115453356B (en) Power equipment operation state monitoring and analyzing method, system, terminal and medium
TWI663569B (en) Quality prediction method for multi-workstation system and system thereof
CN110580019B (en) Edge calculation-oriented equipment calling method and device
CN104991515A (en) Numerical control machine tool full-life-circle importance measurement analysis method
CN113762754A (en) Low-entropy self-adaptive scheduling method for hybrid workshop
JP2002236511A (en) System and method for production control
CN108121305B (en) Dynamic scheduling method and device for job shop tasks
JP2020166407A (en) Model generation device, abnormality occurrence prediction device, abnormality occurrence prediction model generation method and abnormality occurrence prediction method
Maier et al. Automated generation of timing models in distributed production plants
Wenzel et al. Improving the accuracy of cycle time estimation for simulation in volatile manufacturing execution environments
CN118226793B (en) Automatic synchronization station control method and system

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20150729

Termination date: 20170528

CF01 Termination of patent right due to non-payment of annual fee