Operation and maintenance effect evaluation method, system and equipment and storage medium

Abstract

The invention provides an operation and maintenance effect evaluation method, system and device and a storage medium, and relates to the technical field of sewage treatment plant operation and maintenance effect evaluation. The method comprises the steps of determining evaluation indexes; key indexes related to operation and maintenance of the sewage treatment plant are selected; a weight is determined by adopting an analytic hierarchy process, and for each pair of indexes, a score is given according to relative importance, a judgment matrix is formed, and a feature vector and a maximum feature value are calculated; verifying the consistency of the judgment matrix, and ensuring the rationality of evaluation; a fuzzy membership function is determined based on fuzzy mathematics, a fuzzy evaluation matrix is calculated, and then comprehensive evaluation and grade determination are carried out. According to the embodiment of the invention, the index weight is determined through the analytic hierarchy process, and the evaluation data is processed in combination with fuzzy mathematics, so that comprehensive evaluation is carried out, the influence of qualitative and quantitative indexes is comprehensively considered, the method adapts to uncertainty in actual operation, and the overall economic and social benefit capability, the sustainable development capability and the replicability are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of sewage treatment plant operation and maintenance effectiveness evaluation, and in particular to an operation and maintenance effectiveness evaluation method, system, equipment and storage medium. Background Art

[0002] Most of the existing sewage treatment plant operation and maintenance effectiveness evaluation methods only evaluate the sewage treatment plant operation and maintenance effectiveness based on in-plant indicators such as environmental benefits, operation and maintenance cost control, and technical performance. Such methods do not fully consider off-plant indicators such as payment status, public satisfaction, and social contribution. The overall economic and social benefits, sustainable development capabilities, and replicability of sewage treatment plants still need to be further improved. Summary of the invention

[0003] The main purpose of the present invention is to provide an operation and maintenance effectiveness evaluation method, system, equipment and storage medium to solve the technical problems of the current sewage treatment plant operation and maintenance management being not comprehensive enough, the overall economy being not high, and the sustainable development capability and replicability being poor.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is: a method for evaluating operation and maintenance effectiveness, comprising the following steps: S1: Select evaluation indicators and divide them into multiple levels to establish a multi-level operation and maintenance effectiveness evaluation indicator system. The evaluation indicator data of the evaluation indicators include: operation effect, maintenance management, environmental impact and cost control within the sewage treatment plant, and payment, satisfaction and social impact outside the plant; S2: Use the analytic hierarchy process to determine the weight of each evaluation indicator. Specifically, construct a judgment matrix and determine the relative importance of each indicator by scoring or comparing related data; then calculate the eigenvector and maximum eigenvalue of the judgment matrix and perform a consistency test; finally, obtain the weight value of each indicator; S3: Based on fuzzy mathematics and the actual situation of the evaluation indicators, the corresponding fuzzy membership function is determined to normalize and quantify the qualitative and quantitative evaluation indicators; S4: Collect the evaluation index data of the sewage treatment plant, calculate the membership of each index for different evaluation levels according to the fuzzy membership function, and obtain the fuzzy evaluation matrix; S5: Perform weighted operation on the weight of each indicator and the fuzzy evaluation matrix to obtain a comprehensive evaluation result, and determine the operation and maintenance effectiveness level of the current sewage treatment plant based on the comprehensive evaluation result.

[0005] In the preferred solution, a multi-level operation and maintenance effectiveness evaluation indicator system is established in S1, including: Collect relevant data of the sewage treatment plant to be evaluated; Taking the operation and maintenance performance of the sewage treatment plant as the target layer, and the internal and external factors of the plant as the criterion layer, a number of effectiveness evaluation indicators are selected to establish an operation and maintenance effectiveness evaluation system map; Based on the system map, the analytic hierarchy process is used to set the preset discrimination scale of each layer.

[0006] In a preferred embodiment, S2 includes: Compare two adjacent level indicators in the preset discriminant scales of each level, and establish corresponding hierarchical analysis matrices respectively; Then, the yaahp software is used to calculate the weight of each indicator relative to the final goal and to test the consistency of the analysis matrix at each level.

[0007] In the preferred solution, the membership function in S3 is divided into conceptual type, "S" type and parabolic type. The most favorable and most unfavorable conditions for the operation and maintenance of the sewage treatment plant are defined as the upper and lower limits of the critical value of the evaluation factor. After induction, feedback, gradual contraction and concentration, the corresponding membership is finally determined, where: The model formula of “S” type membership function is: ; In the formula, is the actual value of the evaluation factor, and is the threshold of the evaluation factor (where < ), A(x) is the calculated value of the membership function; The parabolic membership function model formula is: ; In the formula, is the actual value of the evaluation factor, , , and is the threshold of the evaluation factor (where < < < ), A(x) is the calculated value of the membership function.

[0008] In the preferred scheme, according to the characteristics of the evaluation index data, the conditions for three-branch decision classification are set, and different membership functions are divided according to the classification results, and the conceptual type and "S" type and "S" type and parabolic type and boundary domain values ​​T1 and T2 are extracted to distinguish between them, so as to establish an operation and maintenance performance evaluation model based on the membership function and the weights of each indicator level analysis.

[0009] An operation and maintenance effectiveness evaluation system, comprising: An evaluation index module is used to select evaluation indicators and divide the evaluation indicators into multiple levels to establish a multi-level operation and maintenance effectiveness evaluation index system. The evaluation index data of the evaluation indicators include: operation effect, maintenance management, environmental impact and cost control within the sewage treatment plant, payment, satisfaction and social impact outside the plant; The weight determination module is used to determine the weight of each evaluation indicator using the hierarchical analysis method. Specifically, the judgment matrix is ​​constructed to determine the relative importance of each indicator by scoring or comparing related data; the eigenvector and maximum eigenvalue of the judgment matrix are calculated, and a consistency test is performed; finally, the weight value of each indicator is obtained; The fuzzy membership module is used to determine the corresponding fuzzy membership function based on fuzzy mathematics and the actual situation of the evaluation indicators, and normalize and quantify the qualitative and quantitative evaluation indicators; The evaluation matrix module is used to collect the evaluation index data of the sewage treatment plant, calculate the membership of each index to different evaluation levels according to the fuzzy membership function, and obtain the fuzzy evaluation matrix; The comprehensive evaluation module is used to perform weighted operation on the weight of each indicator and the fuzzy evaluation matrix to obtain a comprehensive evaluation result, and determine the operation and maintenance effectiveness level of the current sewage treatment plant based on the comprehensive evaluation result.

[0010] A computer device includes but is not limited to one or more processors and a memory, wherein the memory is used to store computer executable programs, and the processor reads part or all of the computer executable programs from the memory and executes them. When the processor executes part or all of the computer executable programs, it can implement part or all of the steps of the operation and maintenance effectiveness evaluation method.

[0011] A computer-readable storage medium comprises: a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the operation and maintenance effectiveness evaluation method is implemented.

[0012] The present invention provides an operation and maintenance effectiveness evaluation method, system, device and storage medium, including selecting key indicators related to the operation and maintenance of a sewage treatment plant, and determining evaluation indicators: selecting key indicators related to the operation and maintenance of a sewage treatment plant; using a hierarchical analysis method to determine weights, and for each pair of indicators, giving scores according to relative importance, forming a judgment matrix, and calculating eigenvectors and maximum eigenvalues; verifying the consistency of the judgment matrix to ensure the rationality of the evaluation; determining a fuzzy membership function based on fuzzy mathematics, calculating a fuzzy evaluation matrix, and then performing a comprehensive evaluation and grade determination. This embodiment determines the indicator weights through a hierarchical analysis method, and then combines fuzzy mathematics to process the evaluation data, thereby performing a comprehensive evaluation, comprehensively considering the influence of qualitative and quantitative indicators, and adapting to the uncertainty in actual operations, thereby improving the overall economic and social benefits, sustainable development capabilities and replicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The present invention will be further described below in conjunction with the accompanying drawings and embodiments: Figure 1 is a flow chart of the method of the present invention; Figure 2 It is a diagram of the sewage treatment plant operation and maintenance effectiveness evaluation system of the present invention; Figure 3 It is a comprehensive evaluation model diagram of the operation and maintenance effectiveness of a sewage treatment plant according to the present invention. DETAILED DESCRIPTION

[0014] Example 1 like Figure 1-3 As shown, a method for evaluating operation and maintenance effectiveness includes the following steps: S1: Select evaluation indicators and divide them into multiple levels to establish a multi-level operation and maintenance effectiveness evaluation indicator system. The evaluation indicator data include: operation effect, maintenance management, environmental impact and cost control within the sewage treatment plant, as well as payment, satisfaction and social impact outside the plant.

[0015] S2: Use the hierarchical analysis method to determine the weight of each evaluation indicator. Specifically, construct a judgment matrix and determine the relative importance of each indicator by scoring or comparing related data; then calculate the eigenvector and maximum eigenvalue of the judgment matrix and perform a consistency test; finally, obtain the weight value of each indicator.

[0016] S3: Based on fuzzy mathematics and according to the actual situation of the evaluation indicators, the corresponding fuzzy membership function is determined to normalize and quantify the qualitative and quantitative evaluation indicators.

[0017] S4: Collect the evaluation index data of the sewage treatment plant, calculate the membership of each index for different evaluation levels according to the fuzzy membership function, and obtain the fuzzy evaluation matrix.

[0018] S5: Perform weighted operation on the weight of each indicator and the fuzzy evaluation matrix to obtain a comprehensive evaluation result, and determine the operation and maintenance effectiveness level of the current sewage treatment plant based on the comprehensive evaluation result.

[0019] This embodiment combines the analytic hierarchy process (AHP) and fuzzy mathematics to form a systematic evaluation framework. First, the evaluation indicators are determined: key indicators related to the operation and maintenance of the sewage treatment plant are selected; the weights are determined by the analytic hierarchy process, and for each pair of indicators, scores are given according to the relative importance to form a judgment matrix, and the eigenvectors and the maximum eigenvalues ​​are calculated; the consistency of the judgment matrix is ​​verified to ensure the rationality of the evaluation; the fuzzy membership function is determined based on fuzzy mathematics, and the fuzzy evaluation matrix is ​​calculated, and then a comprehensive evaluation and grade determination are performed. This embodiment determines the indicator weights through the analytic hierarchy process, and then combines fuzzy mathematics to process the evaluation data, so as to conduct a comprehensive evaluation, comprehensively consider the influence of qualitative and quantitative indicators, and adapt to the uncertainty in actual operations, thereby improving the overall economic and social benefits, sustainable development capabilities and replicability.

[0020] Theoretical basis of this embodiment: The analytic hierarchy process regards performance evaluation as a system and decomposes and compares it. The weight of each level in the analytic hierarchy process will affect the overall result, and the impact of each factor on the result is quantified, which can clearly and clearly measure the relative importance of each indicator. The membership function uses the principle of fuzzy relationship synthesis to quantify factors with unclear boundaries and difficult to quantify, and comprehensively evaluates the status of the evaluated object from multiple factors. At the same time, the membership function uses accurate numbers to process fuzzy evaluation objects, and makes scientific, reasonable and practical evaluations of the information contained.

[0021] Therefore, this embodiment integrates external indicators such as payment status, satisfaction, and social impact into the sewage treatment plant operation and maintenance effectiveness evaluation system, and uses the hierarchical analysis method and fuzzy function comprehensive evaluation method to comprehensively evaluate the sewage treatment plant operation and maintenance effectiveness, which can provide favorable support for the management and decision-making of sewage treatment plants and promote the optimized operation and sustainable development of sewage treatment plants.

[0022] In the preferred solution, a multi-level operation and maintenance effectiveness evaluation indicator system is established in step S1, including: Collect relevant data of the sewage treatment plant to be evaluated.

[0023] Taking the operation and maintenance performance of the sewage treatment plant as the target layer, and the internal and external factors as the criterion layer, a number of effectiveness evaluation indicators are selected to establish an operation and maintenance effectiveness evaluation system map.

[0024] Based on the system map, the analytic hierarchy process is used to set the preset discrimination scale of each layer.

[0025] In this embodiment, relevant data of the sewage treatment plant are collected, including but not limited to: treatment capacity, operating costs, water quality monitoring data, energy consumption data, equipment operation status, operation and maintenance records, and user satisfaction survey results. Data source: The data comes from but is not limited to the internal records, monitoring systems, financial statements and customer feedback of the sewage treatment plant.

[0026] This embodiment establishes an operation and maintenance performance evaluation system map, including: 1) Determine the target layer: Set "wastewater treatment plant operation and maintenance performance" as the target layer of the evaluation system. This is the core goal of the entire evaluation system.

[0027] 2) Set the criteria layer: According to the requirements of the target layer, determine the criteria layer indicators. Generally include: Cost control: Evaluate the management and control of operation and maintenance costs.

[0028] Sewage treatment status: Evaluate the sewage treatment effect, including water quality indicators, treatment capacity, etc.

[0029] Satisfaction: Assess users’ satisfaction with sewage treatment services.

[0030] 3) Select evaluation indicators: Under the criteria layer, select specific evaluation indicators. For example: Cost control: unit processing cost, operating expenses, etc.

[0031] Sewage treatment conditions: effluent water quality compliance rate, treatment efficiency, etc.

[0032] Satisfaction situation: customer satisfaction score, complaint rate, etc.

[0033] 4) Establish a system map: Draw out the target layer, criterion layer and specific evaluation indicators in a hierarchical manner to form an operation and maintenance performance evaluation system map. Figure 2 As shown, the map shows the relationship and structure between each level.

[0034] Through this process, the operation and maintenance effectiveness evaluation index system will have a clear structure and quantitative evaluation standards, providing a solid foundation for subsequent evaluation work.

[0035] The discriminant scale used in this embodiment is shown in Table 1. First, the hierarchical structure of the evaluation indicators is clarified, including the target indicators, sub-indicators and sub-sub-indicators of each level. Comparison of adjacent level indicators: Within each level, adjacent indicators are compared pairwise to establish a hierarchical analysis matrix as shown in Tables 2 to 9. For example, if there are two indicators A and B, evaluate the importance of A relative to B.

[0036] Then select the scale: Use a 1-9 scale system to indicate the importance level of the indicator.

[0037] Table 1 AHP ​​discriminant scale table

[0038] Table 2 First-level impact factor judgment matrix

[0039] Table 3 Secondary impact factor judgment matrix 1

[0040] Table 4 Secondary impact factor judgment matrix 2

[0041] Table 5 Three-level impact factor judgment matrix 1

[0042] Table 6 Three-level impact factor judgment matrix 2

[0043] Table 7 Three-level impact factor judgment matrix 3

[0044] Table 8 Three-level impact factor judgment matrix 4

[0045] Table 9 Judgment matrix of three-level impact factors 5

[0046] In the preferred solution, S2 includes: The adjacent two level indicators in the preset discriminant scale of each level are compared, and the corresponding hierarchical analysis matrix is ​​established respectively.

[0047] Then, the yaahp software is used to calculate the weight of each indicator relative to the final goal and to test the consistency of the analysis matrix at each level.

[0048] According to Table 1, make judgments or data comparisons and fill in each element of the judgment matrix. For example, in the first-level influencing factor judgment matrix in each level analysis matrix table in Table 2, the A1 in-plant factor is more important than the A2 out-plant factor. In the matrix table, A1 is between slightly important and strongly important to A2. The value of A1 to A2 in the matrix is ​​4. The consistency of the judgment matrix is ​​0 (<0.1) tested by yaahp software. The consistency is passed. At this time, the weight of A1 is 0.8 and the weight of A2 is 0.2.

[0049] Calculate the eigenvector and the maximum eigenvalue, and use the eigenvalue and eigenvector method of the matrix to calculate the weight of each indicator. The normalized form of the eigenvector will give the weight of each indicator relative to the target.

[0050] Consistency check: Calculate the consistency ratio (CR) of the judgment matrix to ensure the consistency of the judgment of the matrix. CR should be less than 0.1, indicating that the consistency of the matrix is ​​acceptable. The calculation steps include: 1) Maximum eigenvalue ( ): Calculate the maximum eigenvalue of the judgment matrix.

[0051] 2) Consistency index ( ): Calculate the consistency index .

[0052] 3) Consistency index ( ): Calculate the consistency ratio: , is a random consistency indicator, which depends on the order of the matrix n。

[0053] Then use AHP software (such as yaahp): Input data: Input the judgment matrix into the yaahp software for weight calculation and consistency check.

[0054] Calculate weight: The yaahp software will automatically calculate the weight of each indicator based on the input judgment matrix and give the result of the consistency test.

[0055] Result output: Get the weight value of each indicator and verify the consistency.

[0056] Through the above steps, the weights of each evaluation index can be systematically determined and the consistency of the judgment matrix can be ensured. Using the AHP method for weight calculation can effectively handle complex decision-making problems and provide reliable decision support.

[0057] In the preferred solution, the membership function in step S3 is divided into conceptual type, "S" type and parabolic type. The most favorable and most unfavorable conditions for the operation and maintenance of the sewage treatment plant are defined as the upper and lower limits of the critical value of the evaluation factor. After induction, feedback, gradual contraction and concentration, the corresponding membership is finally determined, where: The model formula of “S” type membership function is: ; In the formula, is the actual value of the evaluation factor, and is the threshold of the evaluation factor (where < ), A(x) is the calculated value of the membership function. When the actual value is below x1, the change in the value of this factor is unfavorable to the operation and maintenance effect of the sewage treatment plant, and does not affect the calculated value of the membership; when the actual value is in the range of x1~x2, the larger the value of this factor is, the more favorable it is to the operation and maintenance effect of the sewage treatment plant, and the larger the calculated value of the membership; when the actual value is above x2, the change in the value of this factor is favorable to the operation and maintenance effect of the sewage treatment plant, and does not affect the calculated value of the membership.

[0058] The parabolic membership function model formula is: ; In the formula, is the actual value of the evaluation factor, , , and is the threshold of the evaluation factor (where < < < ), A(x) is the calculated value of the membership function. When the actual value is below x1 or above x2, the change in the value of this factor is unfavorable to the operation and maintenance results of the sewage treatment plant, and does not affect the calculated value of the membership. When the actual value is in the value range of x1~x3, the larger the value of this factor is, the more favorable it is to the operation and maintenance results of the sewage treatment plant, and the larger the calculated value of the membership. When the actual value is in the value range of x3~x4, the change in the value of this factor is most favorable to the operation and maintenance results of the sewage treatment plant, and does not affect the calculated value of the membership. When the actual value is in the value range of x4~x2, the larger the value of this factor is, the more unfavorable it is to the operation and maintenance results of the sewage treatment plant, and the smaller the calculated value of the membership.

[0059] In this embodiment: 1) Conceptual membership: If the effluent quality of the sewage treatment plant is assessed as “good”, a specific critical value range is set, and then the membership under the “good” state is defined by the set critical value, as shown in Table 10 below. If it is beneficial to the operation and maintenance of the water plant, the membership value is 1; if it is not beneficial to the operation and maintenance of the water plant, the membership value is 0.

[0060] Table 10 Conceptual membership function Not conducive to water plant operation and maintenance effectiveness Conducive to the operation and maintenance of water plants Membership I 0 1 2) “S” type membership: Assuming that the thresholds of “good” water quality are a=70 and b=80, the fuzzy language values ​​of water quality in the range of 70 to 80 will gradually change from “slightly important” to “strongly important”.

[0061] 3) Parabolic membership: Assume that the evaluation threshold of sewage treatment effect is 60 a =60, b =70, c =80, d=90, then the evaluation range from 60 to 70 is "slightly important", 70 to 80 is "relatively important", 80 to 90 is "strongly important", and above 90 is "extremely important".

[0062] Through the membership function, qualitative evaluation indicators can be converted into numerical values ​​that can be processed in fuzzy mathematics, thereby achieving comprehensive evaluation.

[0063] In the preferred scheme, according to the characteristics of the evaluation index data, the conditions for three-branch decision classification are set, and different membership functions are divided according to the classification results, and the conceptual type and "S" type and "S" type and parabolic type and boundary domain values ​​T1 and T2 are extracted to distinguish between them, so as to establish an operation and maintenance performance evaluation model based on the membership function and the weights of each indicator level analysis.

[0064] like Figure 3 As shown, a sewage treatment plant operation and maintenance performance evaluation model is established based on the membership function and the weights of each index hierarchical analysis in steps S1-S4. Finally, in step S5, an existing sewage treatment plant example is used to evaluate the sewage treatment plant operation and maintenance effectiveness evaluation model to verify the accuracy of the model.

[0065] Example 2 In combination with Example 1, a system for evaluating operation and maintenance effectiveness is provided, including: The evaluation index module is used to select evaluation indicators and divide the evaluation indicators into multiple levels to establish a multi-level operation and maintenance effectiveness evaluation index system. The evaluation index data include: operation effect, maintenance management, environmental impact and cost control within the sewage treatment plant, payment, satisfaction and social impact outside the plant.

[0066] The weight determination module is used to determine the weight of each evaluation indicator using the hierarchical analysis method. Specifically, a judgment matrix is ​​constructed to determine the relative importance of each indicator by scoring or comparing related data; the eigenvector and maximum eigenvalue of the judgment matrix are calculated, and a consistency test is performed; finally, the weight value of each indicator is obtained.

[0067] The fuzzy membership module is used to determine the corresponding fuzzy membership function based on fuzzy mathematics and the actual situation of the evaluation indicators, and normalize and quantify the qualitative and quantitative evaluation indicators.

[0068] The evaluation matrix module is used to collect the evaluation index data of the sewage treatment plant, calculate the membership of each index for different evaluation levels according to the fuzzy membership function, and obtain the fuzzy evaluation matrix.

[0069] The comprehensive evaluation module is used to perform weighted operation on the weight of each indicator and the fuzzy evaluation matrix to obtain a comprehensive evaluation result, and determine the operation and maintenance effectiveness level of the current sewage treatment plant based on the comprehensive evaluation result.

[0070] In a preferred embodiment, a computer device includes but is not limited to one or more processors and a memory, the memory is used to store computer executable programs, the processor reads part or all of the computer executable programs from the memory and executes them, and when the processor executes part or all of the computer executable programs, it can implement part or all of the steps of an operation and maintenance effectiveness evaluation method in Example 1.

[0071] In a preferred embodiment, a computer-readable storage medium includes: a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, an operation and maintenance effectiveness evaluation method in Example 1 is implemented.

[0072] The above embodiments are only preferred technical solutions of the present invention and should not be regarded as limiting the present invention. The protection scope of the present invention shall be the technical solutions recorded in the claims, including equivalent replacement solutions of the technical features in the technical solutions recorded in the claims. That is, equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. A method for evaluating operation and maintenance effectiveness, characterized in that: The following steps are involved: S1: Select evaluation indicators and divide them into multiple levels to establish a multi-level operation and maintenance effectiveness evaluation indicator system. The evaluation indicator data of the evaluation indicators include: operation effect, maintenance management, environmental impact and cost control within the sewage treatment plant, and payment, satisfaction and social impact outside the plant; S2: Use the analytic hierarchy process to determine the weight of each evaluation indicator. Specifically, construct a judgment matrix and determine the relative importance of each indicator by scoring or comparing related data; then calculate the eigenvector and maximum eigenvalue of the judgment matrix and perform a consistency test; finally, obtain the weight value of each indicator; S3: Based on fuzzy mathematics and the actual situation of the evaluation indicators, the corresponding fuzzy membership function is determined to normalize and quantify the qualitative and quantitative evaluation indicators; S4: Collect the evaluation index data of the sewage treatment plant, calculate the membership of each index for different evaluation levels according to the fuzzy membership function, and obtain the fuzzy evaluation matrix; S5: Perform weighted operation on the weight of each indicator and the fuzzy evaluation matrix to obtain a comprehensive evaluation result, and determine the operation and maintenance effectiveness level of the current sewage treatment plant based on the comprehensive evaluation result.

2. The operation and maintenance effectiveness evaluation method according to claim 1, characterized in that: In S1, a multi-level operation and maintenance effectiveness evaluation indicator system is established, including: Collect relevant data of the sewage treatment plant to be evaluated; Taking the operation and maintenance performance of the sewage treatment plant as the target layer, and the internal and external factors of the plant as the criterion layer, a number of effectiveness evaluation indicators are selected to establish an operation and maintenance effectiveness evaluation system map; Based on the system map, the analytic hierarchy process is used to set the preset discrimination scale of each layer.

3. The operation and maintenance effectiveness evaluation method according to claim 2, characterized in that: The S2 includes: Compare two adjacent level indicators in the preset discriminant scales of each level, and establish corresponding hierarchical analysis matrices respectively; Then, the yaahp software is used to calculate the weight of each indicator relative to the final goal and to test the consistency of the analysis matrix at each level.

4. The operation and maintenance effectiveness evaluation method according to claim 1, characterized in that: The membership function in S3 is divided into conceptual type, "S" type and parabolic type. The most favorable and most unfavorable conditions for the operation and maintenance of the sewage treatment plant are defined as the upper and lower limits of the critical value of the evaluation factor. After induction, feedback, gradual contraction and concentration, the corresponding membership is finally determined, where: The model formula of "S" type membership function is: ； In the formula, is the actual value of the evaluation factor, and is the threshold of the evaluation factor (where < ), A(x) is the calculated value of the membership function; The parabolic membership function model formula is: ； In the formula, is the actual value of the evaluation factor, , , and is the threshold of the evaluation factor (where < < < ), A(x) is the calculated value of the membership function.

5. The operation and maintenance effectiveness evaluation method according to claim 4 is characterized in that: According to the characteristics of the evaluation index data, the conditions for three-branch decision classification are set, and different membership functions are divided according to the classification results. The boundary domain values ​​T1 and T2 that distinguish the conceptual type from the "S" type and the "S" type from the parabola type are extracted, so as to establish an operation and maintenance performance evaluation model based on the membership function and the weights of each indicator level analysis.

6. An operation and maintenance effectiveness evaluation system, characterized in that: include: An evaluation index module is used to select evaluation indicators and divide the evaluation indicators into multiple levels to establish a multi-level operation and maintenance effectiveness evaluation index system. The evaluation index data of the evaluation indicators include: operation effect, maintenance management, environmental impact and cost control within the sewage treatment plant, payment, satisfaction and social impact outside the plant; The weight determination module is used to determine the weight of each evaluation indicator using the hierarchical analysis method. Specifically, the judgment matrix is ​​constructed to determine the relative importance of each indicator by scoring or comparing related data; the eigenvector and maximum eigenvalue of the judgment matrix are calculated, and a consistency test is performed; finally, the weight value of each indicator is obtained; The fuzzy membership module is used to determine the corresponding fuzzy membership function based on fuzzy mathematics and the actual situation of the evaluation indicators, and normalize and quantify the qualitative and quantitative evaluation indicators; The evaluation matrix module is used to collect the evaluation index data of the sewage treatment plant, calculate the membership of each index to different evaluation levels according to the fuzzy membership function, and obtain the fuzzy evaluation matrix; The comprehensive evaluation module is used to perform weighted operation on the weight of each indicator and the fuzzy evaluation matrix to obtain a comprehensive evaluation result, and determine the operation and maintenance effectiveness level of the current sewage treatment plant based on the comprehensive evaluation result.

7. A computer device, characterized in that: Including but not limited to one or more processors and memories, the memory is used to store computer executable programs, the processor reads part or all of the computer executable programs from the memory and executes them, and when the processor executes part or all of the computer executable programs, it can implement some or all steps of an operation and maintenance effectiveness evaluation method described in claims 1-5.

8. A computer-readable storage medium, characterized in that: include: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for evaluating operation and maintenance effectiveness as described in any one of claims 1 to 5 is implemented.

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