CN107169234B - Comprehensive evaluation method for maintainability of rocker arm system of coal mining machine - Google Patents
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Abstract
The invention provides a comprehensive evaluation method for maintainability of a rocker arm system of a coal mining machine, which is implemented based on a Triangular Fuzzy Analytic Hierarchy Process (TFAHP) and a fuzzy comprehensive evaluation model. The method comprises the steps of firstly establishing a maintainability hierarchical analysis model of the coal mining machine rocker arm system, calculating maintainability weights of all subsystems by using TFAHP, secondly carrying out normalization processing on maintainability qualitative indexes and quantitative data of all the subsystems to obtain maintainability effect values of all the subsystems, processing the qualitative indexes by using a fuzzy comprehensive evaluation model, processing the quantitative data by using a linear mathematical model, then calculating maintainability indexes of all the subsystems, and finally calculating the maintainability indexes by combining the maintainability weights and the maintainability indexes of all the subsystems to obtain the maintainability indexes of the coal mining machine rocker arm system. According to the system-level maintainability index, the optimal scheme in different design schemes can be determined, weak links in the design schemes can be analyzed, and effective improvement measures are provided.
Description
Technical Field
The invention relates to the technical field of maintainability of coal mine mechanical equipment, in particular to a comprehensive evaluation method for maintainability of a rocker arm system of a coal mining machine.
Background
The maintainability is the basic attribute of the equipment, and reflects the capability of quick, convenient and economic maintenance. The rocker arm system of the coal mining machine is used as a main part of the coal mining machine and is also a part with frequent fault, and the quality of the maintenance state of the rocker arm system is directly related to the working efficiency of the whole coal mining machine. During the operation of the coal mining machine, due to the special working environment and the variable working states, the maintenance state of the whole rocker arm system needs to be mastered so as to implement the maintenance timely and efficiently and reduce the maintenance cost of equipment. The existing maintainability model mainly determines the maintenance state of a small simple system, but the comprehensive maintainability evaluation of a large complex coal mining machine rocker arm system integrating machine, electricity and liquid is not mature. Therefore, there is a great need for comprehensive evaluation of the maintenance state of the rocker arm system of the coal mining machine.
Disclosure of Invention
The purpose of the invention is as follows: in order to realize comprehensive evaluation of the maintenance state of the rocker arm system of the coal mining machine and determine a proper design scheme according to the system-level maintainability level, the invention provides a comprehensive evaluation method of the maintainability of the rocker arm system of the coal mining machine.
The technical scheme is as follows: in order to achieve the technical effects, the technical scheme provided by the invention is as follows:
a comprehensive evaluation method for maintainability of a coal mining machine rocker arm system comprises the following steps:
(1) dividing the rocker arm system of the coal mining machine into S subsystems; establishing a maintainability hierarchical analysis model of the coal mining machine rocker arm system by taking S subsystems of the coal mining machine rocker arm system as a scheme layer, taking maintenance evaluation indexes of all preselected subsystems as a criterion layer and taking maintainability indexes of the coal mining machine rocker arm system as a target layer;
(2) on the basis of a maintainability hierarchical analysis model of the coal mining machine rocker arm system, calculating index comprehensive weights of all subsystems to the maintainability indexes of the coal mining machine rocker arm system by adopting a triangular fuzzy hierarchical analysis method, namely the maintainability weights of all subsystems;
(3) dividing the maintainability evaluation index into a qualitative index and a quantitative data index, and respectively calculating the effect values of the qualitative index and the quantitative data index of each subsystem; wherein, the effect value of the qualitative index is calculated by adopting a fuzzy comprehensive evaluation method, and the effect value of the quantitative data index is represented by adopting the following mathematical model:
in the formula, x represents a quantitative data index value; x is the number ofmaxRepresenting the maximum value of the quantitative data index in a preset area range; x is the number ofminRepresenting the minimum value of the quantitative data index in a preset area range; a is an evaluation value range parameter which represents that the value after A is normalized into a percentage system; b represents a shape parameter, and when B is 0, the shape parameter is a linear parameter;
(4) calculating maintainability index M of each subsystemsComprises the following steps:
in the formula, EsIs the efficacy value of the qualitative index of the s-th subsystem, FsThe quantitative data index of the s-th subsystem is the effect value;
(5) calculating the maintainability index M of the coal mining machine rocker arm system as follows:
wherein, ω issRepresenting a maintainability weight for the s-th subsystem; msThe maintainability index of the s-th subsystem is shown.
Further, the serviceability evaluation index includes: accessibility, assembly/disassembly performance, detection and diagnostic performance, maintenance safety, maintenance personnel and repair rates; wherein, the accessibility, the assembling/disassembling performance, the detecting and diagnosing performance, the maintenance safety and the maintenance personnel are qualitative indexes, and the repairing rate is a quantitative data index.
Further, the step of calculating the maintainability weight of each subsystem by adopting a triangular fuzzy analytic hierarchy process comprises the following steps:
(3-1) constructing a triangular fuzzy complementary judgment matrix
In the formula (I), the compound is shown in the specification,
the importance degree of the ith element relative to the jth element in the maintainability hierarchical analysis model is obtained; lijAnd uijAre respectively triangular fuzzy numbers
And satisfies the following upper and lower limits: lij+uji＝1，uij+lji＝1，lii＝0.5，uii＝0.5；mijAs a triangular fuzzy number
The median value of (d);
(3-2) calculating preliminary single-layer fuzzy weight
And (3) performing hierarchical single ordering according to the preliminary single-layer fuzzy weight, namely, assuming that the number of elements of the previous layer is n, calculating the triangular fuzzy weight of the ith element in the next layer relative to some element of the previous layer as follows:
(3-3) establishing a fuzzy consistency probability matrix, and performing defuzzification processing on the single-layer fuzzy weight obtained by calculation in the step two, wherein the step is as follows:
is provided with
Computing
The probability of (c) is:
wherein λ ∈ [0, 1 ]](ii) a When lambda is more than 0.5, the decision maker is in pursuit of risk; λ is 0.5, indicating that the decision maker is risk neutral; when lambda is less than 0.5, the risk of aversion of the decision maker is represented; taking lambda as 0.5, calculating a preliminary complementary likelihood matrix P as (P)ij)n×nAnd converted into a fuzzy consistency likelihood matrix R ═ (R)ij)n×nI.e. by
(3-4) calculating final single-layer weights
Sorting the triangular fuzzy numbers according to the fuzzy consistency likelihood matrix R to obtain a sorting vector of the likelihood matrix, namely the final weight of the hierarchical single sorting of each element:
(3-5) calculating the comprehensive weight
Assuming that the number of second-layer elements of the maintainability hierarchical analysis model is m, the total hierarchical ranking weight is a1，a2，…，am(ii) a The level single ordering weight of each element of the third layer is b1j，b2j，…bSjThen the comprehensive weight ω of each subsystem of the third layersComprises the following steps:
further, the step of calculating the efficacy value of any one of the qualitative indexes of the subsystem by using a fuzzy comprehensive evaluation method comprises the following steps:
(4-1) constructing a fuzzy comprehensive evaluation model of the subsystem, taking qualitative indexes as a factor set of the fuzzy comprehensive evaluation model, and giving a comment set of the fuzzy comprehensive evaluation model in advance;
(4-2) determining a fuzzy evaluation matrix
By fpqAnd representing the membership degree of the p-th factor to the q-th comment in the fuzzy comprehensive evaluation model, wherein the fuzzy evaluation matrix is as follows:
F＝[fpq]P×Q
in the formula, P represents the total number of qualitative indexes in the factor set, and Q represents the total number of comments in the comment set;
(4-3) determining the importance weight as follows:
W＝{w1，w2，…，wP}
w satisfies
(4-4) carrying out fuzzy operation, and calculating a fuzzy comprehensive evaluation set as follows:
wherein the content of the first and second substances,
is a synthesis operator;
(4-5) calculating the effect value of the qualitative index of the subsystem as follows:
Es＝BET
in the formula, EsAnd E is the efficiency value of the qualitative index of the s-th subsystem, and E is the evaluation parameter set corresponding to the comment set.
Has the advantages that: compared with the prior art, the invention has the following advantages: for a large system with complex functions such as a rocker arm of a coal mining machine, the maintainability evaluation is difficult to be directly carried out in a scoring mode of a traditional expert. The invention decomposes the large-scale complex system into the subsystems from top to bottom, has more accurate and reasonable maintainability evaluation on each subsystem, simultaneously comprehensively considers qualitative and quantitative elements, can more scientifically and comprehensively master the maintainability level of the rocker arm system, and is favorable for better selecting a proper design scheme and improving the insufficient scheme.
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FIG. 1 is a schematic diagram of an embodiment of the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings.
First, the maintainability concept is elucidated: maintainability refers to the ability of a product to maintain and recover a state capable of executing a predetermined function under a predetermined use condition, i.e., the probability that a malfunctioning product is repaired within a certain period of time, when maintenance is performed under a predetermined condition and according to a predetermined program and means.
The principle of the invention is shown in fig. 1, and the technical solution of the invention is further explained below with reference to the drawings and the specific embodiments.
The rocker arm system of the coal mining machine is one of the most important components of the coal mining machine, and the maintainability of the rocker arm system directly influences the working efficiency of the whole coal mining machine. The rocker arm system mainly comprises the following four subsystems: cutting system (JS), hydraulic system (YS), electric system (DS), auxiliary system (FS). In the invention, four subsystems of the rocker arm system are used as a scheme layer (a third layer) in a hierarchical analysis model so as to finally obtain the maintainability weight of each subsystem in the whole rocker arm system.
And establishing a maintainability hierarchical analysis model to determine the maintainability index of the coal mining machine rocker arm system.
From the hierarchical analysis model, the maintainability index of the coal mining machine rocker arm system is as follows:
wherein M is the maintainability index of the coal mining machine rocker arm system; omegasRepresenting a maintainability weight for the s-th subsystem; msThe maintainability index of the s-th subsystem is shown.
The next question is how to reasonably and efficiently compute subsystemsMaintainability weight ωsAnd a maintainability index M of each subsystems。
Firstly, the maintainability index M of each subsystem is determineds：
The maintainability evaluation indexes of each subsystem are divided into qualitative indexes and quantitative data indexes, and the two parts are respectively subjected to normalization processing to obtain the effect values, so that the maintainability of each subsystem is conveniently and uniformly evaluated. According to the design criteria and the use requirements of the rocker arm system, the expert opinions are comprehensively considered, and the maintainability evaluation index is selected: accessibility, assembly/disassembly performance, detection and diagnostic performance, maintenance safety, maintenance personnel, 1/MTTR. The maintainability evaluation index can be used as a criterion layer (a second layer) in the hierarchical analysis model to evaluate and score the maintainability of the subsystem.
For qualitative indexes, a fuzzy comprehensive evaluation model can be adopted for processing, and the method comprises the following steps:
determining qualitative index factor set U ═ mu1，μ2，μ3，μ4，μ5And each factor contains a secondary factor set, such as 3 secondary factors mu under factor accessibility1＝{μ11，μ12，μ13}。
The evaluation set and the evaluation result set can be divided into four factors in the determination of the maintenance performance value of the qualitative index, namely v1-you v2-good, v3-middle, v4-poor, then the set of comments V ═ V1，v2，v3，v4}。
Determining fuzzy evaluation matrix
By fpqAnd representing the membership degree of the p factor to the q comment, wherein the fuzzy evaluation matrix is as follows:
F＝[fpq]P×Q
fourthly, determining importance weight W ═ W1，w2，…，wP) And satisfy
The importance weight in this step can be determined by the above-mentioned Triangle Fuzzy Analytic Hierarchy Process (TFAHP).
Fifthly, carrying out fuzzy operation
The fuzzy comprehensive evaluation set of the weighted average model is as follows:
wherein the content of the first and second substances,
referred to as a composition operator. In order to comprehensively consider the influence of each factor on the evaluation result and enable the factors to compensate each other, a multiplication and sum operator (+, -) is selected, namely a weighted average type synthesis operator, and the operation rule of the synthesis operator is equivalent to matrix multiplication.
For a model containing multi-level fuzzy evaluation, a previous level is set to contain m elements, for a next level of each element of the previous level to contain r elements, a next level evaluation result B of each element is calculated firstlyiI is 1, 2, …, m, and a fuzzy evaluation matrix R is constructed as B1，B2，…，Bm]TAnd calculating according to the calculating steps to obtain a final judgment result B.
Sixthly, calculating the maintainability effect value of the qualitative index
The link divides a comment set by adopting a fixed value evaluation parameter, and divides an evaluation parameter set E into {90, 70, 50, 30} corresponding comment set V into { V ═ V }1，v2，v3，v4And (4) the concept of grey number can be introduced to carry out more reasonable numerical division on the comment set.
Then the qualitative index maintainability performance values of the subsystems are as follows:
Es＝BsET
wherein E issMaintaining a performance efficiency value for the qualitative index of the s-th subsystem; b issA qualitative index fuzzy comprehensive evaluation set of the s-th subsystem; e is the set of evaluation parameters for the set of comments.
For quantitative data, the repair rate mu is 1/MTTR, the repair rate mu is taken as a benefit type attribute parameter, and the trend of the quantitative value (score value) of the repair rate mu is in an increasing state along with the increase of the index value.
Can be represented by the following mathematical model:
wherein x represents an evaluation index value; x is the number ofmaxRepresents the maximum value of the evaluation index within the region; x is the number ofminRepresents the minimum value of the evaluation index within the region range; a represents an evaluation value range parameter, and in the percent system, A is 100; b represents a shape parameter, and when 0 is taken, the linear processing method is adopted.
In summary, for the coal mining machine rocker arm system shown in fig. 1, the maintainability index of each subsystem is:
wherein M issThe maintainability index of the s-th subsystem; esMaintaining a performance efficiency value for the qualitative index of the s-th subsystem; fsAnd maintaining the performance efficiency value for the quantitative data of the s-th subsystem.
After the maintainability index of each subsystem is determined, the maintainability weight ω of each subsystem needs to be determinedsThe calculation steps are as follows:
firstly, a triangular fuzzy complementary judgment matrix is constructed, the relative importance degree of the influence factors of the maintainability of each subsystem is judged, and a triangular fuzzy number median scoring rule can be obtained according to the table 1.
TABLE 1 Scoring criterion in triangular blur number
For example, with
Shows each evaluation index (secondLayer) to the weight judgment matrix of the serviceability index of the coal mining machine rocker arm system, then:
every two importance comparisons of the maintainability of the coal mining machine rocker arm system of the target layer (the first layer) are carried out by 6 maintainability evaluation indexes of the criterion layer (the second layer) to obtain 1 fuzzy judgment matrix of 6 multiplied by 6; and carrying out pairwise importance comparison on the criterion layer (second layer) maintainability evaluation indexes by the maintainability of each subsystem of the scheme layer (third layer). 6 4 × 4 fuzzy judgment matrices are obtained.
Secondly, calculating a preliminary single-layer fuzzy weight according to the 7 triangular fuzzy judgment matrixes, and performing hierarchical single-layer sequencing.
Assuming that the number of elements in the previous layer is n, obtaining the triangular fuzzy weight of the ith element relative to the previous layer factor by using a sum-row normalization method as follows:
thirdly, establishing a fuzzy consistency possibility matrix and carrying out defuzzification processing
In order to solve the problems of matrix consistency judgment and fuzzy number sequencing, probability matrix processing is adopted
I.e. the triangular fuzzy number weight is compared pairwise. Is provided with
Then
The probability of (c) is:
wherein λ ∈ [0, 1 ]]. Take lambda0.5, the preliminary complementary likelihood matrix P ═ (P) is calculatedij)n×n. And then converting the preliminary complementary possibility degree matrix into a fuzzy consistency matrix R ═ (R)ij)n×nI.e. by
Fourthly, calculating the final single-layer weight
Sorting the triangular fuzzy numbers according to the fuzzy consistency likelihood matrix R, and obtaining a sorting vector of the likelihood matrix by using a sorting formula, namely the final weight of the index:
calculating the comprehensive weight
Assume that the total ranking weight of the second layer element is a1，a2，…，a6(ii) a The single sorting weight of the third layer element number is b1j，b2j，…，b4jThen the comprehensive weight ω of each subsystemiComprises the following steps:
therefore, the maintainability index of the rocker arm system of the coal mining machine can be obtained.
Based on the maintenance state of the rocker arm system of the coal mining machine, an optimal design scheme can be determined and measures for improving the maintainability of the rocker arm system of the coal mining machine are provided, and the implementation method comprises the following steps:
for several different design schemes, the system-level maintainability index can be calculated according to the method to determine the optimal scheme, weak links of each scheme can be analyzed, and reasonable improvement measures are provided.
When calculating maintainability index of each subsystem, making the membership degree of a certain qualitative index of a certain system to the highest comment 1 or taking certain quantitative data as the maximum value xmaxThe larger the change is, the more the index of the branch system is improved, the maintainability of the coal mining machine rocker arm system can be improved, namely the index is a weak link in the design and can be reasonably improved.
Taking the accessibility of a cutting system (JS) as an example, the membership degree of the accessibility of the JS to the excellent is 1, the maintainability index of the JS system is recalculated, the final maintainability index of the coal mining machine rocker arm system is obtained, the maintainability index is compared with the maintainability index of the original rocker arm system, if the change is large, the accessibility is a weak link of the design, and the maintainability level of the scheme can be effectively improved by improving the accessibility.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.
Claims (3)
1. A comprehensive evaluation method for maintainability of a coal mining machine rocker arm system is characterized by comprising the following steps:
(1) establishing a maintainability hierarchical analysis model of the coal mining machine rocker arm system by taking a cutting system, a hydraulic system, an electrical system and an auxiliary system of the coal mining machine rocker arm system as a scheme layer, taking maintenance evaluation indexes of all pre-selected subsystems as a criterion layer and taking a maintainability index of the coal mining machine rocker arm system as a target layer;
(2) on the basis of a maintainability hierarchical analysis model of a coal mining machine rocker arm system, index comprehensive weights of all subsystems to maintainability indexes of the coal mining machine rocker arm system are calculated by adopting a triangular fuzzy hierarchical analysis method, namely the maintainability weights of all subsystems, and the method specifically comprises the following steps:
1) constructing triangular fuzzy complementary judgment matrix
In the formula (I), the compound is shown in the specification,
the importance degree of the ith element relative to the jth element in the maintainability hierarchical analysis model is obtained; lijAnd uijAre respectively triangular fuzzy numbers
And satisfies the following upper and lower limits: lij+uji＝1，uij+lji＝1，lii＝0.5，uii＝0.5；mijAs a triangular fuzzy number
The median value of (d);
2) calculating preliminary single-layer fuzzy weights
And (3) performing hierarchical single ordering according to the preliminary single-layer fuzzy weight, namely, assuming that the number of elements of the previous layer is n, calculating the triangular fuzzy weight of the ith element in the next layer relative to some element of the previous layer as follows:
3) establishing a fuzzy consistency probability matrix, and performing defuzzification processing on the single-layer fuzzy weight obtained by calculation in the step two, wherein the step two is as follows:
is provided with
Computing
The probability of (c) is:
wherein p isijTo represent
Degree of probability of (l)i、uiRespectively triangular fuzzy weight
Upper and lower bound of (m)iBlurring weights for triangles
The median value of (d); lambda belongs to [0, 1 ]](ii) a When lambda is more than 0.5, the decision maker is in pursuit of risk; λ is 0.5, indicating that the decision maker is risk neutral; when lambda is less than 0.5, the risk of aversion of the decision maker is represented; taking lambda as 0.5, calculating a preliminary complementary likelihood matrix P as (P)ij)n×nAnd converted into a fuzzy consistency likelihood matrix R ═ (R)ij)n×nNamely:
riand rjAre all of the intermediate variables of the process,
pikto represent
Degree of probability of (a), rijIs the ith row and the jth column element in the fuzzy consistency possibility matrix R;
4) calculating final single-layer weights
Sorting the triangular fuzzy numbers according to the fuzzy consistency likelihood matrix R to obtain a sorting vector of the likelihood matrix, namely the final weight of the hierarchical single sorting of each element:
5) calculating the composite weight
Assuming that the number of second-layer elements of the maintainability hierarchical analysis model is m, the total hierarchical ranking weight is a1，a2，…，am(ii) a The level single ordering weight of each element of the third layer is b1j，b2j，…bSjThen the comprehensive weight ω of each subsystem of the third layersComprises the following steps:
(3) dividing the maintainability evaluation index into a qualitative index and a quantitative data index, and respectively calculating the effect values of the qualitative index and the quantitative data index of each subsystem; wherein, the effect value of the qualitative index is calculated by adopting a fuzzy comprehensive evaluation method, and the effect value of the quantitative data index is represented by adopting the following mathematical model:
in the formula, x represents a quantitative data index value; x is the number ofmaxRepresenting the maximum value of the quantitative data index in a preset area range; x is the number ofminRepresenting the minimum value of the quantitative data index in a preset area range; a is an evaluation value range parameter which represents that the value after A is normalized into a percentage system; b represents a shape parameter, and when B is 0, the shape parameter is a linear parameter;
(4) calculating maintainability index M of each subsystemsComprises the following steps:
in the formula, EsIs the efficacy value of the qualitative index of the s-th subsystem，FsThe quantitative data index of the s-th subsystem is the effect value; s represents the total number of subsystems;
(5) calculating the maintainability index M of the coal mining machine rocker arm system as follows:
wherein, ω issRepresenting a maintainability weight for the s-th subsystem; msThe maintainability index of the s-th subsystem is shown.
2. The comprehensive serviceability evaluation method for the shearer ranging arm system as recited in claim 1, wherein the serviceability evaluation index includes: accessibility, assembly/disassembly performance, detection and diagnostic performance, maintenance safety, maintenance personnel and repair rates; wherein, the accessibility, the assembling/disassembling performance, the detecting and diagnosing performance, the maintenance safety and the maintenance personnel are qualitative indexes, and the repairing rate is a quantitative data index.
3. The comprehensive serviceability evaluation method for the shearer ranging arm system as recited in claim 1, wherein the step of calculating the effectiveness value of any one of the subsystem qualitative indexes by the fuzzy comprehensive evaluation method comprises:
(4-1) constructing a fuzzy comprehensive evaluation model of the subsystem, taking qualitative indexes as a factor set of the fuzzy comprehensive evaluation model, and giving a comment set of the fuzzy comprehensive evaluation model in advance;
(4-2) determining a fuzzy evaluation matrix
By fpqAnd representing the membership degree of the p-th factor to the q-th comment in the fuzzy comprehensive evaluation model, wherein the fuzzy evaluation matrix is as follows:
F＝[fpq]P×Q
in the formula, P represents the total number of qualitative indexes in the factor set, and Q represents the total number of comments in the comment set;
(4-3) determining the importance weight as follows:
W＝{w1，w2，…，wP}
w satisfies
(4-4) carrying out fuzzy operation, and calculating a fuzzy comprehensive evaluation set as follows:
wherein the content of the first and second substances,
is a synthesis operator;
(4-5) calculating the effect value of the qualitative index of the subsystem as follows:
Es＝BET
in the formula, EsAnd E is the efficiency value of the qualitative index of the s-th subsystem, and E is the evaluation parameter set corresponding to the comment set.
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