A method for analyzing factors affecting equipment operation and maintenance based on ISM and ANP

Abstract

The present invention provides an equipment operation and maintenance influencing factor analysis method based on ISM and ANP. The analysis method specifically comprises the following steps: obtaining the influencing factors of equipment operation and maintenance through an exhaustive method and constructing an influencing factor set; constructing a direct influence matrix through an ISM algorithm, calculating a comprehensive influence matrix, and obtaining a hierarchical topology map corresponding to the influencing factor set; obtaining hierarchical results of the influencing factors according to the hierarchical topology map, constructing an ANP model, performing a weight ratio analysis on all influencing factors in the hierarchical topology map based on the obtained hierarchical results of the influencing factors based on the ANP model, obtaining the weight corresponding to each influencing factor in the hierarchical topology map according to the weight ratio analysis result, and obtaining the action path of each influencing factor in the hierarchical topology map through the ANP model structure and the hierarchical topology map. The present invention can obtain the key influencing factors of equipment operation and maintenance and the corresponding hierarchical relationships and action paths, effectively improving the efficiency of equipment operation and maintenance.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment operation and maintenance, and in particular to an analysis method of equipment operation and maintenance influencing factors based on ISM and ANP. Background Art

[0002] As a key carrier for my country's clean energy development, the construction of ultra-high voltage (UHV) power grids is rapidly advancing, and my country is gradually achieving full grid coverage. During the construction of UHV power grids, the quality of UHV equipment directly determines the safe and stable operation of the grid. Therefore, the operation and maintenance management of UHV equipment has become a crucial factor in its successful development. Effective analysis of factors influencing equipment operation and maintenance can effectively improve equipment operation and maintenance efficiency, thereby enhancing the safe and stable operation of the UHV power grid. Existing methods for analyzing factors influencing UHV equipment operation and maintenance primarily rely on correlation analysis. The results of these methods only capture the correlation between each influencing factor and the equipment, but fail to capture the correlations between different influencing factors. Consequently, the impact of these factors on equipment operation and maintenance remains unknown during equipment operation and maintenance. Consequently, equipment operation and maintenance efficiency is low when these results are analyzed based on these methods. Summary of the Invention

[0003] The purpose of the present invention is to overcome the shortcomings of the existing technology and provide an equipment operation and maintenance influencing factor analysis method based on ISM and ANP. By performing equipment operation and maintenance influencing factor analysis through ISM and ANP, the key influencing factors of equipment operation and maintenance and the hierarchical relationship of the key influencing factors can be obtained, thereby determining the action path of the key influencing factors. The problem of low equipment operation and maintenance efficiency due to the inability to obtain the correlation between different influencing factors in the existing equipment operation and maintenance influencing factor analysis method can be effectively solved, so that the equipment operation and maintenance efficiency can be significantly improved.

[0004] The purpose of the present invention is achieved through the following technical solutions:

[0005] A method for analyzing factors affecting equipment operation and maintenance based on ISM and ANP includes the following steps:

[0006] Step 1: Obtain the influencing factors of equipment operation and maintenance through exhaustive method and construct an influencing factor set;

[0007] Step 2: Use the ISM algorithm to construct a direct impact matrix based on the influencing factor set, and calculate the comprehensive impact matrix based on the direct impact matrix to obtain the hierarchical topology map corresponding to the influencing factor set;

[0008] Step three: obtain the hierarchical results of the influencing factors according to the hierarchical topology map, construct an ANP model, and perform a weight ratio analysis on all the influencing factors in the hierarchical topology map based on the obtained hierarchical results of the influencing factors based on the ANP model. According to the weight ratio analysis results, obtain the weight corresponding to each influencing factor in the hierarchical topology map, and obtain the action path of each influencing factor in the hierarchical topology map through the ANP model structure and the hierarchical topology map.

[0009] Furthermore, in step 1, after obtaining the influencing factors of equipment operation and maintenance according to the exhaustive method, the key influencing factors among the influencing factors are selected through the expert experience method, and the influencing factor set is constructed based on the selected key influencing factors.

[0010] Furthermore, in step 2, the direct impact matrix is ​​constructed according to the influencing factor set through the ISM algorithm, and the specific process of calculating the comprehensive impact matrix based on the direct impact matrix is: the direct impact matrix is ​​constructed according to the correlation between each key influencing factor in the influencing factor set through the expert scoring method, the direct impact matrix is ​​normalized, and the comprehensive impact matrix calculation result is obtained according to the normalized direct impact matrix through the comprehensive impact matrix calculation formula.

[0011] Furthermore, the comprehensive impact matrix calculation formula is expressed as follows:

[0012] T=lim k→∞ M+M 2 +…+M k =M(EM) -1 ;

[0013]

[0014] Where: T is the comprehensive influence matrix, M is the normalized direct influence matrix, E is the n-dimensional unit matrix, n is the number of key influencing factors in the influencing factor set, dm ij is the impact value of the i-th key influencing factor on the j-th key influencing factor in the direct impact matrix.

[0015] Furthermore, the specific process of obtaining the hierarchical topological diagram corresponding to the influencing factor set in step 2 is: obtaining the influence index of each key influencing factor based on the calculation result of the comprehensive influence matrix, and obtaining the priori result based on the influence index of each key influencing factor, constructing the factor adjacency matrix based on the priori result, calculating the reachable matrix by performing continuous multiplication on the adjacency matrix, and respectively calculating the reachable set, antecedent set and common set based on the reachable matrix, dividing all the key influencing factors in the influencing factor set into a hierarchical structure according to the hierarchical extraction rule with result priority, and obtaining the hierarchical structure diagram corresponding to the influencing factor set.

[0016] Furthermore, the influence index of each key influencing factor includes influence degree, influenced degree, centrality and cause degree.

[0017] Furthermore, in step three, an ANP model is constructed. The specific process of weight proportion analysis of all influencing factors in the hierarchical topology map based on the ANP model according to the hierarchical results of the influencing factors is as follows: the control layer and the network layer of the ANP model are determined according to the hierarchical results of the influencing factors, the key influencing factors at the top layer in the hierarchical topology map are set as the control layer, and the remaining key influencing factors are set as the network layer, and the key influencing factors of each layer constitute a group of the network layer, the key influencing factors in the control layer are used as the target criteria, one of the groups in the network layer is selected, and the key influencing factors in the selected group are used as secondary criteria, a judgment matrix is ​​constructed, and the key influencing factors in each group are obtained according to the judgment matrix. The degree of influence of the influencing factors on the sub-criteria is obtained, and the corresponding sorting vector is obtained. A group is reselected as the sub-criteria, and the corresponding sorting vector is obtained again, until the corresponding sorting vector of each group as the sub-criteria is obtained. The super-matrix is ​​obtained based on all the obtained sorting vectors, and the importance of each key influencing factor corresponding to the target criterion to the sub-criteria is compared, and a group is reselected as the sub-criteria until the importance comparison result corresponding to each group is obtained. The weighted matrix is ​​obtained based on the comparison results corresponding to all groups, and the factors in the super-matrix are weighted according to the weighted matrix to obtain the weighted super-matrix, and the limit of the weighted super-matrix is ​​calculated. The weight of each key influencing factor is determined according to the calculation results.

[0018] Furthermore, the influencing factors obtained by the exhaustive method in step one include regional difference factors, equipment factors, user structure and asset structure factors, and regional environment factors.

[0019] The beneficial effects of the present invention are:

[0020] The ISM algorithm can be used to perform a hierarchical analysis of influencing factors, obtaining hierarchical results of the influencing factors. The ANP model can then be used to perform a weighted analysis based on the hierarchical results. The weighted analysis results can more intuitively determine the importance of the influencing factors. Furthermore, the calculation results of the ISM algorithm and the ANP model can be used to determine the correlation between influencing factors and their degree of influence. Based on these correlations and degrees of influence, the path of action of each influencing factor can be determined. When equipment operation and maintenance is required, the order of operation and maintenance can be determined based on the importance and path of action of the influencing factors, resulting in higher efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic diagram of a process of the present invention;

[0022] Figure 2This is a cause-effect diagram of an influencing factor in an embodiment of the present invention;

[0023] Figure 3 This is a schematic diagram of a hierarchical topology of influencing factors according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The present invention will be further described below with reference to the accompanying drawings and examples.

[0025] Example:

[0026] A method for analyzing factors affecting equipment operation and maintenance based on ISM and ANP, such as Figure 1 As shown, the following steps are included:

[0027] Step 1: Obtain the influencing factors of equipment operation and maintenance through exhaustive method and construct an influencing factor set;

[0028] Step 2: Use the ISM algorithm to construct a direct impact matrix based on the influencing factor set, and calculate the comprehensive impact matrix based on the direct impact matrix to obtain the hierarchical topology map corresponding to the influencing factor set;

[0029] Step three: obtain the hierarchical results of the influencing factors according to the hierarchical topology map, construct an ANP model, and perform a weight ratio analysis on all the influencing factors in the hierarchical topology map based on the obtained hierarchical results of the influencing factors based on the ANP model. According to the weight ratio analysis results, obtain the weight corresponding to each influencing factor in the hierarchical topology map, and obtain the action path of each influencing factor in the hierarchical topology map through the ANP model structure and the hierarchical topology map.

[0030] After exhaustively identifying the factors influencing equipment operation and maintenance in step 1, we then use expert experience to select key factors from these factors and construct an influencing factor set based on these key factors. Specifically, the factors identified through exhaustive analysis include regional differences, equipment factors, user and asset structure factors, and regional environmental factors.

[0031] The regional difference factor is S1.

[0032] The equipment factors specifically include equipment regeneration rate S2, equipment quality S3, equipment operation and maintenance strategy S4, live working coverage S5 and equipment pollution degree S6.

[0033] Customer structure and asset structure are key factors influencing equipment operation and maintenance. Asset structure reflects load characteristics such as the layout and matching relationship between power supply and load, as well as power supply reliability. Key influencing factors include asset size and structure (S7), grid structure (S8), and distribution network automation level (S9). Customer structure primarily reflects differences in customer load demands and electricity usage structures. Key influencing factors include customer number (S10) and customer type and structure (S11).

[0034] Regional environmental factors include regional natural geographical conditions, regional economic development level, urbanization level, and other related factors. Key descriptive indicators include regional economic scale (S12), key support special tasks (S13), urbanization level (S14), and natural geographical conditions (S15).

[0035] Specifically, the key influencing factors included in the constructed influencing factor set are regional difference factors S1, equipment regeneration rate S2, equipment quality S3, equipment operation and maintenance strategy S4, live working coverage S5, equipment pollution degree S6, asset scale and structure S7, grid structure S8, distribution network automation level S9, number of users S10, user type and structure S11, regional economic scale S12, key guarantee special tasks S13, urbanization level S14 and natural geographical conditions S15.

[0036] In step 2, the direct impact matrix is ​​constructed based on the influencing factor set using the ISM algorithm, and the specific process of calculating the comprehensive impact matrix based on the direct impact matrix is ​​as follows: the direct impact matrix is ​​constructed based on the correlation between each key influencing factor in the influencing factor set using the expert scoring method. The expert scoring of each factor in the constructed direct impact factor matrix is ​​shown in Table 1:

[0037] Table 1 Expert scores for each factor in the direct influencing factor matrix

[0038]

[0039]

[0040] The direct influence matrix is ​​normalized, specifically, normalized by using the row sum maximum method.

[0041] The calculation results of the comprehensive impact matrix are obtained according to the normalized direct impact matrix through the comprehensive impact matrix calculation formula.

[0042] The comprehensive impact matrix calculation formula is expressed as follows:

[0043] T=lim k→∞ M+M 2 +…+M k =M(EM) -1 ;

[0044]

[0045] Where: T is the comprehensive influence matrix, M is the normalized direct influence matrix, E is the n-dimensional unit matrix, n is the number of key influencing factors in the influencing factor set, dm ijis the impact value of the i-th key influencing factor on the j-th key influencing factor in the direct impact matrix.

[0046] The specific process of obtaining the hierarchical topology corresponding to the influencing factor set in step 2 is: obtaining the influence index of each key influencing factor according to the calculation result of the comprehensive influence matrix.

[0047] The influence indicators of each key influencing factor include influence degree I, influenced degree ID, centrality C and cause degree R.

[0048] The influence degree I refers to the sum of the values ​​of each row in the comprehensive influence matrix, which represents the comprehensive influence value of the influencing factors corresponding to each row on all other influencing factors. Its calculation formula is: Among them, I i is the comprehensive impact value of the influencing factor corresponding to the i-th row of the comprehensive impact matrix on all other influencing factors, n is the number of columns in the comprehensive impact matrix, that is, the number of influencing factors, j is the influencing factor corresponding to the j-th column of the comprehensive impact matrix, t ij is the impact value of the influencing factor corresponding to the i-th row on the influencing factor corresponding to the j-th column of the comprehensive impact matrix;

[0049] The impact degree ID refers to the sum of the column values ​​of the comprehensive impact matrix, which represents the comprehensive impact value of all other factors on the corresponding factors in each row. The calculation formula is: Among them, ID j is the comprehensive impact value of the influencing factor corresponding to the jth column of the comprehensive impact matrix subjected to all other influencing factors, t ji is the impact value of the influencing factor corresponding to the jth column of the comprehensive influence matrix on the influencing factor corresponding to the ith row;

[0050] The centrality C indicates the position of the influencing factor in the evaluation index system and the size of its role, that is, the degree of importance.

[0051] The causal degree R indicates the degree of influence of the influencing factor on other influencing factors, and R i =I i +ID i , where R i The causal degree of the influencing factor in the i-th row and i-th column of the comprehensive influence matrix is ​​shown in the figure below. When R>0, the corresponding influencing factor is the cause factor, and in other cases, the corresponding influencing factor is the result factor. The causal degree analysis of each influencing factor listed in Table 1 is performed, and the causal result diagram of the influencing factor is shown in the figure below. Figure 2 As shown. Figure 2It can be seen that the overall influencing factors can be divided into four layers: essential factors, transition factors, and surface factors. The influencing factors in the middle two layers are transition factors. The essential factors, namely the fourth layer, include regional economic scale (S12). Among the transition factors, the third layer includes the number of users (S10), user type and structure (S11), urbanization level (S14), and natural geographical conditions (S15). The fourth layer includes equipment regeneration rate (S2), equipment quality (S3), equipment operation and maintenance strategy (S4), live working coverage (S5), equipment pollution level (S6), asset scale and structure (S7), power grid structure (S8), distribution network automation level (S9), and key guarantee special tasks (S13). The surface factors, namely the first layer, include regional differences.

[0052] And obtain the prior results based on the impact index of each key influencing factor, which is the cause and effect analysis result of the influencing factor. Construct the factor adjacency matrix A based on the prior results. When two influencing factors S i and S j When there is no binary relationship between them, the corresponding element A in the factor adjacency matrix A ij is 0, otherwise, the corresponding element A in the factor adjacency matrix A ij is 1.

[0053] The reachable matrix R is calculated by performing continuous multiplication on the adjacency matrix, that is, B k-1 ≠B k =B k+1 =R, where the matrix B is equal to the factored adjacency matrix A plus the identity matrix.

[0054] According to the reachable matrix, the reachable set R(S i ), antecedent set Q(S i ) and the common set T(S i ), where the common set T(S i )=R(S i )∩Q(S i ).

[0055] According to the hierarchical extraction rule of result priority, all key influencing factors in the influencing factor set are divided into hierarchical structures, that is, T(S i )=R(S i ), obtain the hierarchical structure diagram corresponding to the influencing factor set, the hierarchical structure diagram is as follows Figure 3 shown.

[0056] In step 3, the ANP model is constructed. The specific process of weight proportion analysis of all influencing factors in the hierarchical topology map based on the ANP model and the obtained hierarchical results of the influencing factors is as follows: the control layer and network layer of the ANP model are determined according to the hierarchical results of the influencing factors, and the key influencing factors at the top layer in the hierarchical topology map are set as the control layer C0, that is, the key influencing factors corresponding to the control layer C0 are the regional difference factors S1. The remaining key influencing factors are set as the network layer, and the key influencing factors of each layer constitute a group of the network layer, that is, the network layer includes groups C0, C1, ..., C N , where N is the number of layers. The i-th packet C in the network layer i The key factors influencing the il ,…,e inj , i=1,2,…,N, l=1,2,…,n i , n i is the number of influencing factors constructed in the i-th level.

[0057] The key influencing factor in the control layer, that is, the regional difference factor S1, is used as the target criterion P1, and one of the groups C in the network layer is selected. j , select group C j Key influencing factors within jl (l=1,2,…,n j , n j is the number of influencing factors constructed in the jth level) as the secondary criterion P n , group one of the unselected i The key factors affecting e jl The influence of the two groups was compared indirectly, and group C was constructed based on the comparison results. i The corresponding judgment matrix is ​​obtained, and the judgment matrix corresponding to each unselected group is obtained in turn.

[0058] According to the judgment matrix, the key influencing factors in the grouping are obtained for the secondary criteria P n The degree of influence, construct the sorting vector, group C i The matrix of the corresponding sorting vectors is:

[0059]

[0060] Among them, W ij The column vector in is the group C i One of the key factors and the group C j The ranking vector of the influence degree of key influencing factors in , For group C i nth i Key factors affecting group C j nthj The degree of influence of the key influencing factors.

[0061] When group C i The key influencing factors are not in the group C j If the key influencing factors have an impact, the corresponding value is assigned to 0.

[0062] Reselect a group as the sub-criteria and re-obtain the corresponding sorting vector until the sorting vector corresponding to each group as the sub-criteria is obtained.

[0063] The super matrix W is obtained based on all the sorted vectors obtained, and its expression is:

[0064]

[0065] Among them, W NN When the Nth group is used as the secondary criterion, the sorting vector calculation result corresponding to the Nth group is obtained.

[0066] Compare the key influencing factors corresponding to the target criterion P1 to the sub-criterion P n When the key influencing factor is irrelevant to the secondary criterion Pn, the corresponding component is 0. The weighting matrix A is obtained according to the comparison result. The expression of the weighting matrix A is:

[0067]

[0068] Among them, a NN The Nth key influencing factor in the target criterion P1 is used as the sub-criterion P for each N groups. n The corresponding importance comparison results are shown in Figure 2.

[0069] The factors in the supermatrix W are weighted according to the weighting matrix A to obtain the weighted supermatrix a ij is the value of the element in the i-th row and j-th column of the weighted matrix A. Calculate the weighted supermatrix The weight of each key influencing factor is determined based on the calculation results.

[0070] According to the weighted super matrix The weight values ​​of each key influencing factor obtained from the limit calculation results are shown in Table 2:

[0071] Table 2 Weight values ​​of key influencing factors

[0072]

[0073] Depend on Figure 2Table 2 can be used to analyze the action path of each influencing factor. Taking the action path of regional economic scale S12 as an example, regional economic scale S12 is the essential factor with the largest weight. It will affect the key influencing factors of user quantity S10 and user type and structure S11. After the user quantity S10 and user type and structure S11 are affected and changed, they will continue to affect the equipment regeneration rate S2, equipment quality S3, asset scale and structure S7, power grid structure S8 and distribution network automation level S9. After the equipment regeneration rate S2, equipment quality S3, asset scale and structure S7, power grid structure S8 and distribution network automation level S9 are affected and changed, they will have a certain degree of impact on the regional difference factor S1.

[0074] The embodiment described above is only a preferred solution of the present invention and does not limit the present invention in any form. Other variations and modifications are possible without exceeding the technical solution described in the claims.

Claims

1. A method for analyzing factors affecting equipment operation and maintenance based on ISM and ANP, characterized by: The following steps are involved: Step 1: Obtain the influencing factors of equipment operation and maintenance through exhaustive method and construct an influencing factor set; Step 2: Use the ISM algorithm to construct a direct impact matrix based on the influencing factor set, and calculate the comprehensive impact matrix based on the direct impact matrix to obtain the hierarchical topology map corresponding to the influencing factor set; Step 3: Obtain hierarchical results of influencing factors according to the hierarchical topology map, construct an ANP model, perform weight ratio analysis on all influencing factors in the hierarchical topology map based on the obtained hierarchical results of influencing factors based on the ANP model, obtain the weight corresponding to each influencing factor in the hierarchical topology map according to the weight ratio analysis result, and obtain the action path of each influencing factor in the hierarchical topology map through the ANP model structure and the hierarchical topology map; In step 2, the direct impact matrix is ​​constructed based on the influencing factor set using the ISM algorithm, and the specific process of calculating the comprehensive impact matrix based on the direct impact matrix is ​​as follows: the direct impact matrix is ​​constructed based on the correlation between each key influencing factor in the influencing factor set using the expert scoring method, the direct impact matrix is ​​normalized, and the comprehensive impact matrix calculation result is obtained based on the normalized direct impact matrix using the comprehensive impact matrix calculation formula; The comprehensive impact matrix calculation formula is expressed as follows: Where: T is the comprehensive influence matrix, M is the normalized direct influence matrix, E is the n-dimensional unit matrix, n is the number of key influencing factors in the influencing factor set, is the impact value of the i-th key influencing factor on the j-th key influencing factor in the direct impact matrix; The specific process of obtaining the hierarchical topological diagram corresponding to the influencing factor set in step 2 is: obtain the influence index of each key influencing factor based on the calculation result of the comprehensive influence matrix, and obtain the priori result based on the influence index of each key influencing factor, construct the factor adjacency matrix based on the priori result, calculate the reachable matrix by performing continuous multiplication on the adjacency matrix, and calculate the reachable set, antecedent set and common set respectively according to the reachable matrix, divide all the key influencing factors in the influencing factor set into a hierarchical structure according to the hierarchical extraction rule with result priority, and obtain the hierarchical structure diagram corresponding to the influencing factor set.

2. The method for analyzing factors affecting equipment operation and maintenance based on ISM and ANP according to claim 1, characterized in that: In step 1, after obtaining the influencing factors of equipment operation and maintenance according to the exhaustive method, the key influencing factors among the influencing factors are selected through the expert experience method, and the influencing factor set is constructed based on the selected key influencing factors.

3. The method for analyzing factors affecting equipment operation and maintenance based on ISM and ANP according to claim 1, characterized in that: The influence indicators of each key influencing factor include influence degree, influence degree, centrality and cause degree.

4. The method for analyzing factors affecting equipment operation and maintenance based on ISM and ANP according to claim 1, characterized in that: In step three, the ANP model is constructed. The specific process of weight proportion analysis of all influencing factors in the hierarchical topology diagram based on the ANP model according to the hierarchical results of the influencing factors is as follows: the control layer and network layer of the ANP model are determined according to the hierarchical results of the influencing factors, the key influencing factors at the top layer in the hierarchical topology diagram are set as the control layer, and the remaining key influencing factors are set as the network layer. The key influencing factors of each layer constitute a group of the network layer. The key influencing factors in the control layer are used as the target criteria, one of the groups in the network layer is selected, and the key influencing factors in the selected group are used as secondary criteria. A judgment matrix is ​​constructed, and the key influencing factors in each group are obtained according to the judgment matrix. The degree of influence of the factors on the sub-criteria is obtained, and the corresponding sorting vector is obtained. A group is re-selected as the sub-criteria, and the corresponding sorting vector is obtained again until the sorting vector corresponding to each group is obtained as the sub-criteria. The super-matrix is ​​obtained according to all the sorting vectors obtained, and the importance of each key influencing factor corresponding to the target criterion to the sub-criteria is compared. A group is re-selected as the sub-criteria until the importance comparison result corresponding to each group is obtained. The weighted matrix is ​​obtained according to the comparison results corresponding to all groups. The factors in the super-matrix are weighted according to the weighted matrix to obtain the weighted super-matrix, and the limit of the weighted super-matrix is ​​calculated. The weight of each key influencing factor is determined according to the calculation result.

5. The method for analyzing factors affecting equipment operation and maintenance based on ISM and ANP according to claim 2, characterized in that: The influencing factors obtained through the exhaustive method in step one include regional difference factors, equipment factors, user structure and asset structure factors, and regional environment factors.

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