CN115293601A - Risk evaluation method for underground working face equipment removing process based on fuzzy analytic hierarchy process - Google Patents
Risk evaluation method for underground working face equipment removing process based on fuzzy analytic hierarchy process Download PDFInfo
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Abstract
The invention discloses a method for evaluating the risk of removing a process for underground working face equipment based on a fuzzy analytic hierarchy process, which comprises the following steps of applying a working hazard analysis method (JHA), identifying hazard sources from four aspects of personnel, machines, environment and management in the process of process application, and constructing a process application risk evaluation index system; constructing a fuzzy judgment matrix of each hierarchy element according to the relative importance ratio of each risk factor; calculating the weight value of each risk factor by an analytic hierarchy process, and carrying out consistency check on the fuzzy judgment matrix; and establishing a proper comment set according to the risk hazard degree during the use of the process equipment. The method has the advantages of high accuracy, high reliability and the like, and provides a scientific reference for preventing equipment removal risk accidents.
Description
Technical Field
The invention relates to the field of coal mine risk assessment, in particular to a method for evaluating the risk of removing a process of underground working face equipment based on a fuzzy analytic hierarchy process.
Background
The removal and moving of the fully mechanized coal mining face is a complex system project, and the removal work is difficult. In the application process of engineering practice, due to the fact that complex geological conditions and working environments exist on a fully mechanized mining working face, the process is affected by a plurality of risk factors in a removing link, and a large number of bearing bodies are concentrated in narrow space, so that danger is easily caused when people operate process equipment, and serious casualties and great property loss are caused. Therefore, effective identification and security evaluation of risk factors would be highly desirable.
At present, the conventional qualitative or semi-quantitative analysis method is mainly used for the risk evaluation of the underground working face equipment removal process. There are several disadvantages in the practical application of the equipment removal process: the methods do not integrally consider harmful factors from the perspective of a system, and cannot achieve the expected control effect in engineering practice; some methods can be used for comprehensive hazard evaluation including a large number of objects and complex information, can make more use of knowledge information, and meet consistency of thinking to some extent. But the sorting speed is relatively slow; the evaluation method in the prior art does not fully consider the visual impression of the practical personnel, has the evaluation standard which is not specific and objective, and cannot realize the effect of wide popularization in engineering.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides the method for evaluating the risk of the underground working surface equipment removing process based on the fuzzy analytic hierarchy process, the method makes full use of various hazard factor data influencing the environment and equipment use in the removing link, and the method has the advantages of high realization efficiency and reliable evaluation result.
Under the condition, the fuzzy analytic hierarchy process is combined with the fuzzy evaluation and the analytic hierarchy process, so that the problems are well solved, namely risk assessment of the process when the underground working surface equipment is removed is carried out, and then preventive measures aiming at specific safety risks can be made, and the process equipment is safely and efficiently removed.
The technical problem of the invention is mainly solved by the following technical scheme:
the method comprises the steps of constructing a process application risk evaluation index system, calculating the weight of each evaluation index in the evaluation system by combining an analytic hierarchy process and a fuzzy mathematical theory, and obtaining process risk grade evaluation when the underground working surface equipment is removed based on data and weight corresponding to each hazard factor.
The method specifically comprises the following steps:
(1) Constructing a risk evaluation model of process application: simulating and identifying the safety risk of a process application link by using a work hazard analysis method (JHA), and constructing a risk evaluation model of the process application according to an index system;
(2) Determining a judgment matrix: constructing a pairwise comparison fuzzy judgment matrix according to the relative importance ratio of each risk factor;
(3) And (3) carrying out consistency check on the judgment matrix: and combining the analytic hierarchy process scale values, calculating relevant parameters of the evaluation index judgment matrix, including the weight W of each factor, the maximum characteristic value and the consistency ratio C.R., and respectively obtaining consistency test results of each judgment matrix.
(4) And (3) constructing a comment set: in order to divide the risk degree of the risk more finely, a comment set with five hazard levels of safety, general, danger and danger is constructed;
(5) Establishing a membership matrix: objectively evaluating the hazard degree of each index in an index system by referring to the actual experience of coal mine workers and review suggestions of some experts, establishing a membership matrix according with the actual situation, and carrying out normalization processing on the result;
(6) Single/multifactor fuzzy evaluation: performing single-factor fuzzy evaluation and multi-factor fuzzy evaluation from the four aspects of human, machine, ring and pipe respectively;
(7) Calculating and determining the hazard grade of each risk factor in the fuzzy comprehensive evaluation model: based on the fuzzy evaluation result and the maximum membership principle, calculating to obtain the hazard level of the risk factors influencing the process application link in the fuzzy comprehensive evaluation model.
Furthermore, in the step (1), a working hazard analysis method (JHA) is applied, a proper evaluation method is selected, and through simulation analysis, the risk source identification of the process application link is carried out in the aspects of personnel, machines, environment and management, and specifically, the risk source identification is divided into a risk type, a safety risk factor and a specific risk. The established process application risk evaluation index system comprises 4 first-level indexes: personnel, machines, environment, management; 13 secondary indexes: driver violations, personnel standing, operational proficiency, design defects, equipment fires, circuit aging, work space, environmental changes, noise and vibration effects, lighting and color, driver violation of regulatory regulations, task ambiguity, and regulatory confusion.
Further, constructing a judgment matrix according to a 1-9 scaling method in the step (2);
the 1-9 scale is as follows:
the scale is 1, indicating that two elements are of equal importance compared;
the scale is 3, indicating that the former is slightly more important than the latter in comparison with the two elements;
the scale is 5, indicating that the former is significantly more important than the latter in comparison to the two elements;
the scale is 7, indicating that the former is more important than the latter in comparison to the two elements;
the scale is 9, indicating that the former is extremely important compared to the latter;
the scale is 2,4,6,8, which indicates that the importance is in the middle of the above-mentioned adjacent judgment;
reciprocal, the scale of importance of the latter over the former, compared to the two elements.
Through calculation and analysis, a pairwise comparison judgment matrix is obtained as follows:
wherein, a ij Represents the element X i With the element X j And (4) the degree of membership of the important relationship when comparing with the element Y of the previous layer. I.e. element X i With the element X j Relative to the previous layerWhen element Y is compared, X i And X j With a degree of membership that is a fuzzy relationship "the former is much more important than the latter".
Further, when the consistency of the judgment matrix is checked in the step (3), the analytic hierarchy process scale value is used for calculating relevant parameters of the evaluation index judgment matrix, wherein the relevant parameters comprise the weight W of each factor, the maximum characteristic value, the consistency ratio C.R, and the like. And judging whether the consistency check result of each judgment matrix meets C.R. <0.1. If c.r. <0.1, it is reasonable to obtain each weight index.
Specifically, the following equations (1) to (7) are shown:
W＝(W 1 ,W 2 ...W n ) T (4)
wherein, (AW) i Representing the ith component of the vector AW.
Further, in step (4), in order to divide the risk degree of the risk generated more finely, a comment set with five hazard levels of safety, general, danger and danger is constructed. Wherein, the safe value range is 0<P is less than or equal to 20, the safe value range is 20< -P is less than or equal to 40, the general value range is 40< -P is less than or equal to 60, the dangerous value range is 60< -P is less than or equal to 80, and the dangerous value range is 80< -P is less than or equal to 100.
Further, in step (5), a membership matrix according with the actual situation is established, wherein:
membership degree vector
Membership matrix R = (R) 1 ,R 2 ,...,R n ) T ＝(r ij )，
And (3) sorting and analyzing the data corresponding to each hazard factor, and normalizing by using a formula (8):
further, in the step (6), single/multi-factor evaluation is carried out on four aspects of human, machine, ring and pipe, and the harmfulness evaluation of the process application and the multi-factor fuzzy evaluation of the risk harmfulness degree of the process application based on the four factors of the human, machine, ring and pipe are respectively obtained; wherein the formula used for evaluating the hazard of the single factor to the process application is B i ＝W i Xr, the formula used for the hazard assessment of multifactorial for process applications is B = W · R = W · B · i ]。
Further, in the step (7), the hazard degree of each index is obtained according to the maximum membership principle, and further the hazard level of the risk factors of the process application link in the fuzzy comprehensive evaluation model is calculated.
The invention has the following beneficial effects:
in order to solve the limitation of the traditional analytic hierarchy process, the analytic hierarchy process is combined with the fuzzy mathematical theory, the fuzzy theory is determined through a judgment matrix with the scale of 0.1-0.9, the subjective influence brought by the analytic hierarchy process is weakened, and meanwhile, the complex characteristic value calculation and consistency check generated in the analytic hierarchy process are avoided;
according to the method, the risk evaluation method for removing the underground working face equipment is established according to the fuzzy analytic hierarchy process, so that coal mine enterprises can carry out quantitative analysis on hazard factors according to actual underground equipment moving projects of the coal mine enterprises, scientific basis is provided for application of removing the underground working face equipment, subjectivity, blindness and unsafety of the equipment in the removing process are further reduced, and scientific and reasonable risk management strategies are adopted for risk avoidance.
Drawings
FIG. 1 is a flow chart of the evaluation method of the present invention.
FIG. 2 is a schematic diagram of an evaluation index system of the hazard factors of the present invention.
The specific implementation mode is as follows:
the invention provides a fuzzy analytic hierarchy process based underground working surface equipment removal process risk evaluation method. The invention is described in detail below with reference to the figures and specific embodiments.
The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments. As shown in fig. 1, the method comprises the steps of:
(1) analyzing and determining a risk source of process application by using a work hazard analysis method (JHA), and constructing a process application risk evaluation index system;
a work hazard analysis method (JHA) is applied, and through simulation analysis, the danger sources existing in the process application link are identified from the aspects of personnel, machines, environment and management, so that an application link danger source identification table is obtained, and is shown in table 1.
TABLE 1 identification of dangerous sources in process application links
And constructing a process application risk evaluation index system, wherein the process application risk evaluation index system comprises 4 primary indexes: personnel (B1), equipment (B2), environment (B3), management (B4); 13 secondary indexes: driver violations (C1), personnel standing (C2), operational proficiency (C3), design defects (C4), equipment fires (C5), circuit aging (C6), work space (C7), environmental changes (C8), noise and vibration effects (C9), lighting and color (C10), driver violation management regulations (C11), task ambiguity (C12), and management confusion (C13). And constructing a risk evaluation model of the process application according to an index system, wherein the total target layer is A, the criterion layers are B1 to B4, and the scheme layers are C1 to C13.
(2) Constructing a fuzzy judgment matrix of each hierarchy element according to the relative importance ratio of each risk factor;
when the collected data is sorted and analyzed, the data with large deviation is removed, then the relative importance of each factor is compared from the residual data, and a judgment matrix is constructed by utilizing a 1-9 scale method. Specifically, as shown in table 2.
Table 2 decision matrix scale definition table
(3) Calculating the weight value of each risk factor by an analytic hierarchy process, and carrying out consistency check on the fuzzy judgment matrix;
combining the analytic hierarchy process scale values, calculating relevant parameters of an evaluation index judgment matrix, and calculating the weight W of each factor and the maximum characteristic value lambda max Consistency ratio c.r. etc. The correlation equations that can be used are shown in equations (1) - (7).
Wherein M is i Representing the scores of all items in the judgment matrix;
wherein the content of the first and second substances,
represents the nth root of Mi;
wherein, W i Representing the normalized result of the vector represented by Wi;
W＝(W 1 ,W 2 ...W n ) T (4)
wherein W represents the final feature vector result;
wherein λ is max Represents the maximum feature root;
wherein c.i. represents a consistency index;
wherein c.r. represents the consistency ratio;
(4) in the engineering practice process, establishing a proper comment set according to the risk hazard degree;
the set of comments constructed is the criticality of the risk, i.e., V 1 The comment set is set to five levels, i.e. V 1 And (4) the terms of each grade and their specific requirements are shown in table 3.
TABLE 3 set of risk occurrence hazard comments for Process applications
(5) Determining the actual hazard degree of each index in an index system by referring to the actual experience of coal mine workers and review suggestions of some experts, and then performing normalization processing to construct a membership matrix;
membership degree vector
Membership matrix
R＝(R 1 ,R 2 ,...,R n ) T ＝(r ij ) (10)
(6) Single-factor fuzzy evaluation and multi-factor fuzzy evaluation are respectively carried out from four aspects of 'human', 'machine', 'ring' and 'tube';
relative weight W of each factor obtained from scheme layer (bottom layer) i And a process application risk hazard degree membership matrix, so that evaluation results of different first-level indexes on each comment set can be obtained.
The formula used for evaluating the hazard of the single factor to the process application is B i ＝W i ×R i Respectively solving the harmfulness evaluation results of four primary indexes of human, machine, ring and pipe;
<xnotran> B = W · R = W · [ B </xnotran> i ]And calculating the harmfulness evaluation result of the comprehensive factors of the four primary indexes of human, machine, ring and pipe.
(7) And establishing a risk factor fuzzy comprehensive evaluation model of the process application link according to the maximum membership principle and carrying out grade evaluation.
And calculating a comprehensive fuzzy evaluation result. And obtaining a comprehensive fuzzy evaluation result according to the multi-factor fuzzy evaluation result of the risk and harm degree of the process application.
According to the needs, the comprehensive fuzzy evaluation results of the risk factors corresponding to the primary indexes and the secondary indexes can be calculated respectively.
According to the maximum membership principle, a risk factor fuzzy comprehensive evaluation model of a process application link is established and grade evaluation is carried out, so that a scientific reference is provided for preventing equipment from removing risk accidents.
TABLE 4 fuzzy comprehensive evaluation grade result of risk factors of process application links
Comprehensive analysis, the evaluation method of the model is a method for converting qualitative analysis into quantitative analysis and combining the qualitative analysis with the quantitative analysis, and can provide more accurate results and more targeted evaluation opinions. And the evaluation method has pertinence and scientificity compared with the traditional method by using a fuzzy hierarchical analysis method, and can weaken the influence generated by subjective evaluation better. The method has the advantages of high accuracy, high reliability and the like, and can improve the accuracy of safety evaluation in the underground working face equipment removing process.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It is to be understood that appropriate changes or modifications may be made thereto by those of ordinary skill in the art without creative efforts. Such modifications and refinements are also to be considered within the scope of the present invention. Therefore, the technical solutions that can be obtained by a person skilled in the art through logical analysis and reasoning on the basis of the prior art according to the concept of the present invention should be within the scope of protection determined by the claims.
Claims (9)
1. The method for evaluating the process risk of removing the underground working face equipment based on the fuzzy analytic hierarchy process is characterized by comprising the following steps of:
(1) Constructing a risk evaluation model of process application: simulating and identifying the safety risk of a process application link by using a work hazard analysis method (JHA), constructing a process application risk evaluation index system, and establishing a risk evaluation model of process application;
(2) Determining a judgment matrix: constructing a pairwise comparison fuzzy judgment matrix according to the relative importance ratio of each risk factor;
(3) And (3) carrying out consistency check on the judgment matrix: combining the analytic hierarchy process scale values, calculating relevant parameters of the evaluation index judgment matrix, including the weight W of each factor and the maximum characteristic value lambda max Respectively obtaining consistency test results of the judgment matrixes according to the consistency ratio C.R.;
(4) And (3) constructing a comment set: in order to divide the risk degree of the risk more finely, a comment set with five hazard levels of safety, general, danger and danger is constructed;
(5) Establishing a membership matrix: objectively evaluating the hazard degree of each index in an index system by referring to the actual experience of coal mine workers and review suggestions of some experts, establishing a membership matrix according with the actual situation, and carrying out normalization processing on the result;
(6) Single/multifactor fuzzy evaluation: performing single-factor fuzzy evaluation and multi-factor fuzzy evaluation from the four aspects of human, machine, ring and pipe respectively;
(7) Calculating and determining the hazard grade of each risk factor in the fuzzy comprehensive evaluation model: based on the fuzzy evaluation result and the maximum membership principle, calculating to obtain the hazard level of risk factors influencing the process application link in the fuzzy comprehensive evaluation model.
2. The method for evaluating risk of a downhole working surface equipment removal process based on the fuzzy analytic hierarchy process of claim 1, wherein: in the step (1), a work hazard analysis method (JHA) is used for identifying the hazard source of the process application link from the aspects of personnel, machines, environment and management through simulation analysis, and a process application risk evaluation index system is constructed.
3. The method for evaluating risk of a downhole working surface equipment removal process based on the fuzzy analytic hierarchy process of claim 1, wherein: when the judgment matrix is constructed in the step (2), constructing according to a 1-9 scale method;
the 1-9 scale is as follows:
the scale is 1, indicating that two elements are of equal importance compared;
the scale is 3, indicating that the former is slightly more important than the latter in comparison with the two elements;
the scale is 5, indicating that the former is significantly more important than the latter in comparison to the two elements;
the scale is 7, indicating that the former is more important than the latter in comparison to the two elements;
the scale is 9, indicating that the former is extremely important compared to the latter;
the scale is 2,4,6,8, which indicates that the importance is in the middle of the above-mentioned adjacent judgment;
reciprocal, the scale of importance of the latter over the former compared to the two elements;
through calculation and analysis, a pairwise comparison judgment matrix is obtained as follows:
wherein, a ij Represents the element X i With the element X j And (4) the degree of membership of the important relationship when comparing with the element Y of the previous layer.
4. The method for evaluating risk of a downhole working surface equipment removal process based on the fuzzy analytic hierarchy process of claim 1, wherein: in the step (3), the analytic hierarchy process scale value is utilized to calculate the relevant parameters of the evaluation index judgment matrix, including the weight W of each factor and the maximum characteristic value lambda max The consistency ratio C.R. and the like carry out consistency check of the judgment matrix and verify the rationality of each index parameter; specifically, the following equations (1) to (7) are shown:
W＝(W 1 ,W 2 ...W n ) T (4)
wherein, (AW) i Represents the ith component of the vector AW; when C.R.<When the weight is 0.1, the weight indexes are reasonable.
5. The method for evaluating risk of a downhole working surface equipment removal process based on the fuzzy analytic hierarchy process of claim 1, wherein: in the step (4), in order to divide the generated risk hazard degree more carefully, a comment set of five hazard levels of safety, general, danger and danger is constructed, and the range of the value range of each hazard level is determined; wherein, the safe value range is 0<P is less than or equal to 20, the safe value range is 20< -P is less than or equal to 40, the general value range is 40< -P is less than or equal to 60, the dangerous value range is 60< -P is less than or equal to 80, and the dangerous value range is 80< -P is less than or equal to 100.
6. The method for evaluating risk of a downhole working surface equipment removal process based on the fuzzy analytic hierarchy process of claim 1, wherein: in step (5), a membership matrix conforming to the actual situation is established, wherein:
membership vector:
membership matrix:
R＝(R 1 ,R 2 ,...,R n ) T ＝(r ij )
and (3) sorting and analyzing the data corresponding to each hazard factor, and normalizing by using a formula (8):
7. the method for evaluating risk of a downhole working surface equipment removal process based on the fuzzy analytic hierarchy process of claim 1, wherein: in the step (6), single/multi-factor evaluation is carried out from the four aspects of human, machine, ring and pipe, and the harmfulness evaluation of the process application and the single/multi-factor fuzzy evaluation of the risk hazard degree of the process application based on the four factors of human, machine, ring and pipe are respectively obtained, wherein:
the formula used for the hazard assessment of the single factor for the process application is:
B i ＝W i ·R i
the hazard assessment for a process application using multiple factors uses the formula:
B＝W·R＝W·[B i ]。
8. the method for evaluating risk of a downhole working surface equipment removal process based on the fuzzy analytic hierarchy process of claim 1, wherein: in the step (7), the hazard degree of each index is obtained according to the maximum membership principle, and then the hazard level of the risk factors of the process application link in the fuzzy comprehensive evaluation model is calculated.
9. The method for evaluating risk of equipment removal process of a downhole working face based on the fuzzy analytic hierarchy process of claim 2, wherein: identifying the danger source of the process application link from the aspects of personnel, machines, environment and management, and specifically classifying the danger source into a risk type, a safety risk factor and a specific risk; the established process application risk evaluation index system comprises 4 first-level indexes: personnel, machines, environment, management; 13 secondary indexes: driver violations, personnel standing, operational proficiency, design defects, equipment fires, circuit aging, work space, environmental changes, noise and vibration effects, lighting and color, driver violation of regulatory regulations, task ambiguity, and regulatory confusion.
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| CN115879654A (en) * | 2023-03-03 | 2023-03-31 | 山东科技大学 | Method for predicting stability and evaluating reliability of underground roadway |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115879654A (en) * | 2023-03-03 | 2023-03-31 | 山东科技大学 | Method for predicting stability and evaluating reliability of underground roadway |
| CN115879654B (en) * | 2023-03-03 | 2023-05-16 | 山东科技大学 | Underground roadway stability prediction and reliability evaluation method |
| CN117034042A (en) * | 2023-10-08 | 2023-11-10 | 北京德众国良环保科技有限公司 | Processing method and system for analyzing pollutant hazard based on big data platform |
| CN117034042B (en) * | 2023-10-08 | 2023-12-22 | 北京德众国良环保科技有限公司 | Processing method and system for analyzing pollutant hazard based on big data platform |
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