Full-life-cycle safety evaluation method and system, electronic equipment and storage medium

Abstract

The invention provides a full-life-cycle safety evaluation method and system, electronic equipment and a storage medium, and relates to the technical field of safety evaluation.The method comprises the steps that a safety risk evaluation index factor set and a safety risk comment set of a pressure steel pipe are constructed, the safety risk evaluation index factor set comprises a plurality of evaluation index factors influencing the whole life cycle safety of the pressure steel pipe, and the safety risk comment set comprises a plurality of safety risk levels of the whole life cycle; determining the weight of each evaluation index factor based on an analytic hierarchy process to obtain a target weight set, calculating the membership degree of each evaluation index factor to the security risk comment set by adopting a fuzzy comprehensive evaluation method, and generating a fuzzy evaluation matrix; performing composite operation on the target weight set and the fuzzy evaluation matrix to obtain a fuzzy comprehensive evaluation set; and determining a target safety risk level of the pressure steel pipe according to the fuzzy comprehensive evaluation set. By implementing the technical scheme provided by the invention, the effect of improving the accuracy of safety evaluation is achieved.

Description

Technical Field

[0001] The present application relates to the field of safety assessment technology, and specifically to a full life cycle safety assessment method, system, electronic device and storage medium. Background Art

[0002] In hydropower station projects, the safe operation of penstocks directly affects power generation efficiency and facility safety. In the safety management of penstocks in hydropower stations, the safety evaluation methods in related technologies mainly rely on empirical judgment and local detection, lacking systematicity and comprehensiveness. They usually only focus on a certain stage of the penstock (such as the design or operation stage) and ignore its dynamic changes throughout its life cycle. In addition, the safety of penstocks is affected by many factors, including design rationality, manufacturing quality, installation process, operating environment, and scrapping. There are complex interrelationships between these factors, and many factors are ambiguous and uncertain, making it difficult to directly describe them with precise numerical values, and difficult to evaluate them through simple quantitative methods. Therefore, when faced with these complex, ambiguous and dynamically changing safety influencing factors, existing technologies are often unable to provide accurate and effective safety evaluation results, resulting in the difficulty in timely discovery and treatment of safety hazards, which brings potential risks to the safe operation of hydropower stations. Summary of the Invention

[0003] In order to solve the above technical problems, the present application provides a full life cycle safety assessment method, system, electronic device and storage medium.

[0004] In the first aspect, the present application provides a full life cycle safety assessment method, which is applied to the pressure steel pipe of a hydropower station, including: constructing a safety risk assessment index factor set and a safety risk review set for the pressure steel pipe, wherein the safety risk assessment index factor set includes multiple evaluation index factors that affect the safety of the pressure steel pipe throughout its life cycle, and the safety risk review set includes multiple safety risk levels of the pressure steel pipe throughout its life cycle; determining the weights of each evaluation index factor in the safety risk assessment index factor set based on the hierarchical analysis method to obtain a target weight set, and using a fuzzy comprehensive evaluation method to calculate the membership of each evaluation index factor to the safety risk review set to generate a fuzzy evaluation matrix; performing a compound operation on the target weight set and the fuzzy evaluation matrix to obtain a fuzzy comprehensive evaluation set; and determining the target safety risk level of the pressure steel pipe based on the fuzzy comprehensive evaluation set.

[0005] By adopting the above technical scheme, a safety risk evaluation index factor set of multiple evaluation index factors affecting the safety of the penstock throughout its life cycle and a safety risk evaluation set of multiple safety risk levels are constructed, which can comprehensively consider the safety influencing factors that dynamically change during the entire life cycle of the penstock; the hierarchical analysis method is used to determine the weights of each evaluation index factor to obtain a target weight set, and the fuzzy comprehensive evaluation method is used to calculate the membership of each evaluation index factor to the safety risk evaluation set to obtain a fuzzy evaluation matrix, which can handle complex, fuzzy and difficult to accurately quantify safety influencing factors; a composite operation is performed on the target weight set and the fuzzy evaluation matrix to obtain a fuzzy comprehensive evaluation set, and then the target safety risk level is determined based on the fuzzy comprehensive evaluation, which can provide accurate and scientific safety evaluation results, timely discover and deal with safety hazards, ensure the safe operation of the penstock of the hydropower station, and achieve the effect of improving the accuracy of the safety evaluation of the penstock.

[0006] Optionally, before constructing the safety risk assessment indicator factor set for pressure steel pipes, the above method also includes: constructing a hierarchical structure model, the model including a target layer, a criterion layer and an indicator layer, wherein the target layer is used to characterize the overall goal of the safety risk assessment of the pressure steel pipe throughout its life cycle, the criterion layer includes first-level factors for five stages: design, manufacturing, installation, operation, and scrapping, the indicator layer includes a safety risk assessment indicator factor set, and the safety risk assessment indicator factor set includes the influencing factors corresponding to each first-level factor.

[0007] By adopting the above technical solution and constructing a hierarchical structure model, we can systematically and comprehensively sort out the factors that affect the safety of the penstock throughout its entire life cycle. Starting from the overall goal, we can refine the first-level factors and their corresponding influencing factors at each stage, laying the foundation for the subsequent determination of the evaluation index factor weights and evaluation, making the safety evaluation more targeted and accurate, and solving the problem that related technologies lack systematicity and comprehensiveness and ignore the dynamic changes throughout the entire life cycle.

[0008] Optionally, the first-level factors include the design stage, manufacturing stage, installation stage, operation stage and scrapping stage; among them, the influencing factors corresponding to the design stage include: structural design rationality, material and wall thickness selection, stress distribution and concentration, pipeline strength; the influencing factors corresponding to the manufacturing stage include: manufacturing process, production environment, manufacturing quality; the influencing factors corresponding to the installation stage include: installation process, installation docking quality, installation weld quality; the influencing factors corresponding to the operation stage include: operation stability, corrosion mechanism damage, concrete structure damage, weld deformation and damage, on-site monitoring and maintenance, pipeline damage; the influencing factors corresponding to the scrapping stage include: safety assessment, safety margin, and scrapping standards.

[0009] By adopting the above technical solution, the primary factors and their corresponding influencing factors at different stages of the life cycle of the penstock and a more complete set of safety risk assessment indicators are identified, and a more complete set of safety risk assessment indicators is constructed. Taking into account the safety influencing factors of all aspects of the entire process from design to scrapping of the penstock, the evaluation is made more systematic and comprehensive, and the safety risks of the penstock throughout its life cycle can be assessed more accurately.

[0010] Optionally, the weights of each evaluation index factor in the safety risk assessment index factor set are determined based on the hierarchical analysis method to obtain a target weight set, including: constructing a first judgment matrix of the criterion layer using the nine-level scaling method; determining the weights of each first-level factor based on the first judgment matrix to obtain a first weight vector; constructing a judgment matrix of the index layer using the nine-level scaling method, the judgment matrix of the index layer includes multiple second judgment matrices, wherein each first-level factor corresponds to a second judgment matrix; determining the local weights of each influencing factor included in each first-level factor based on the multiple second judgment matrices to obtain multiple second weight vectors; obtaining a target weight set based on the first weight vector and the multiple second weight vectors, wherein the target weight set includes the global weights of each influencing factor in the safety risk assessment index factor set in the full life cycle safety assessment.

[0011] By adopting the above technical solution, it is possible to assign reasonable weights to multiple evaluation index factors that affect the safety of hydropower station penstocks throughout their entire life cycle, thereby more scientifically and accurately considering the degree of influence of various factors on the safety risk of penstocks, making subsequent safety evaluation results more accurate and reliable. This solves the problem that existing technologies are difficult to quantify and evaluate complex, ambiguous and dynamically changing safety influencing factors, and can timely discover and deal with safety hazards.

[0012] Optionally, a target weight set is obtained based on the first weight vector and multiple second weight vectors, including: the first weight vector is W = [W1, W2, W3, W4, W5], the i-th second weight vector is Qi = [Qi1, ..., Qim], where 1≤i≤5, Wi represents the weight of the i-th first-level factor, Qi represents the second weight vector of multiple influencing factors corresponding to the i-th first-level factor in the criterion layer; the global weight of each influencing factor contained in the i-th first-level factor is calculated according to the following formula: aik = Wi × Qik, aik represents all weights of the k-th influencing factor contained in the i-th first-level factor, m represents the number of influencing factors included in the i-th first-level factor, 1≤k≤m.

[0013] By adopting the above technical solution, the weight of the first-level factor and the local weights of multiple influencing factors included in each first-level factor are combined, and the global weight of each influencing factor in the full life cycle safety evaluation can be accurately calculated, making the weight distribution of each influencing factor in the full life cycle safety evaluation of the penstock more scientific and reasonable, which helps to improve the accuracy of the safety evaluation results.

[0014] Optionally, the weights of each first-level factor are determined according to the first judgment matrix to obtain a first weight vector, including: normalizing the first judgment matrix by column to obtain a processed judgment matrix; averaging the elements in each row of the processed judgment matrix to obtain an initial weight vector, wherein the initial weight vector includes the initial weights of each first-level factor, and each row of elements corresponds to a first-level factor; if the consistency test of the first judgment matrix passes, the initial weight vector is determined as the first weight vector.

[0015] By adopting the above technical solution, the first judgment matrix is ​​first normalized by columns and the average of the elements in each row is calculated to obtain the initial weight vector. Then, a consistency test is performed to ensure that the first judgment matrix is ​​reasonable, and finally the first weight vector of the first-level factor is determined. This makes the determination of the first-level factor weight more scientific, reasonable and reliable, thereby improving the accuracy of the life cycle safety assessment method in judging the safety risk level of the hydropower station penstock.

[0016] Optionally, the consistency test includes calculating a consistency ratio CR, and when CR is less than 0.1, it is determined that the first judgment matrix passes the consistency test; wherein the specific steps of the consistency test include: calculating the maximum characteristic root λ of the first judgment matrix ax And consistency index CI=(λ ax -n) / (n-1), where n represents the number of first-level factors in the criterion layer, A represents the first judgment matrix, W represents the initial weight vector, and Wi represents the weight corresponding to the i-th first-level factor; the random consistency index RI corresponding to n is obtained by looking up the table, and the consistency ratio CR = CI / RI is calculated; if CR ≥ 0.1, the scale value of the first judgment matrix is ​​adjusted until CR < 0.1; if CR < 0.1, the first judgment matrix is ​​judged to have passed the consistency test.

[0017] By adopting the above technical solution, in the process of determining the weights of the first-level factors after constructing the hierarchical structure model, the first judgment matrix is ​​subjected to consistency testing and the consistency ratio is calculated to ensure the logical rationality and reliability of the judgment matrix; when the consistency ratio does not meet the requirements, the scale value of the first judgment matrix is ​​adjusted to make the weight distribution of the first-level factors more scientific and objective, thereby ensuring the accuracy of the target safety risk level determined by the full life cycle safety assessment method.

[0018] Optionally, determining a target safety risk level of the penstock based on the fuzzy comprehensive evaluation set includes: determining the safety risk level corresponding to the maximum value in the fuzzy comprehensive evaluation set as the target safety risk level based on the maximum membership principle.

[0019] By adopting the above technical solution, the target safety risk level of the pressure steel pipe can be accurately and conveniently determined based on the fuzzy comprehensive evaluation set, thereby improving the scientificity and accuracy of the full life cycle safety evaluation method in determining the safety risk level.

[0020] Optionally, the indicator layer includes a dynamic update mechanism to iteratively modify the fuzzy membership function and weight parameters based on historical data.

[0021] By adopting the above technical solution, a hierarchical structure model is constructed to make the safety evaluation more systematic. Multiple evaluation index factors that affect safety throughout the life cycle are taken into consideration to make the evaluation more comprehensive. The combination of hierarchical analysis method and fuzzy comprehensive evaluation method can handle complex and fuzzy safety influencing factors and obtain membership and weights. After composite calculation, the fuzzy comprehensive evaluation set is obtained to determine the target safety risk level. The dynamic update mechanism of the indicator layer can iteratively correct the fuzzy membership function and weight parameters according to historical data, so that the safety evaluation can adapt to the dynamic changes in the entire life cycle of the pressure steel pipe and improve the accuracy and scientificity of the evaluation results.

[0022] Optionally, the above method also includes: the fuzzy evaluation matrix and the fuzzy comprehensive evaluation set are dynamically updated according to real-time monitoring data, specifically including: regularly collecting target operation data of the operation phase; recalculating the membership of corresponding evaluation index factors based on the target operation data to obtain an updated fuzzy evaluation matrix; updating the fuzzy comprehensive evaluation set according to the updated fuzzy evaluation matrix, and outputting the current safety level.

[0023] By adopting the above technical solution, the fuzzy evaluation matrix and fuzzy comprehensive evaluation set can be regularly updated based on the target operation data of the operation phase, so as to realize real-time assessment of the target safety risk level of the penstock, timely reflect the dynamic changes of the penstock during operation, improve the accuracy and timeliness of the safety evaluation results, and enable safety hazards to be discovered and handled in a timely manner.

[0024] Optionally, the security risk review set includes: security level, basic security level and unsafe level.

[0025] By adopting the above technical solution, the safety risk level classification of the entire life cycle of the penstock is clarified, which facilitates more detailed and accurate assessment and judgment of the safety status of the penstock.

[0026] Optionally, the above method further includes: when the target security risk level is a basic security level, outputting a list of specific indicators that need to be maintained; when the target security risk level is an unsafe level, triggering an alarm.

[0027] By adopting the above technical solution, when the target safety risk level is the basic safety level, a list of specific indicators that need to be maintained will be output, allowing staff to carry out targeted maintenance on the penstock and eliminate potential safety hazards in a timely manner; when the target safety risk level is the unsafe level, an alarm will be triggered, which can promptly remind staff to take measures to reduce the probability of safety accidents and ensure the safe operation of the penstock of the hydropower station.

[0028] In a second aspect of the present application, a full life cycle safety assessment system is also provided for executing any of the foregoing full life cycle safety assessment methods, including: a construction module for constructing a safety risk assessment index factor set and a safety risk review set for pressure steel pipes, wherein the safety risk assessment index factor set includes multiple evaluation index factors that affect the full life cycle safety of pressure steel pipes, and the safety risk review set includes multiple safety risk levels of the full life cycle of pressure steel pipes; a processing module for determining the weights of each evaluation index factor in the safety risk assessment index factor set based on the hierarchical analysis method to obtain a target weight set, and using a fuzzy comprehensive evaluation method to calculate the membership of each evaluation index factor to the safety risk review set to generate a fuzzy evaluation matrix; an operation module for performing a compound operation on the target weight set and the fuzzy evaluation matrix to obtain a fuzzy comprehensive evaluation set; and a determination module for determining the target safety risk level of the pressure steel pipe based on the fuzzy comprehensive evaluation set.

[0029] In a third aspect of the present application, an electronic device is provided, comprising a memory and a processor, wherein a computer program is stored in the memory, and the processor implements any one of the above method steps when executing the program.

[0030] In a fourth aspect of the present application, a computer-readable storage medium is further provided. The computer-readable storage medium stores instructions. When the instructions are executed, any one of the above method steps is performed.

[0031] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: 1. Constructing a safety risk evaluation index factor set for multiple evaluation index factors affecting the safety of penstocks throughout their entire life cycle and a safety risk evaluation set for multiple safety risk levels, this approach can comprehensively consider the dynamically changing safety influencing factors within the penstock's entire life cycle. Using the analytic hierarchy process to determine the weights of each evaluation index factor to obtain a target weight set, and using the fuzzy comprehensive evaluation method to calculate the membership of each evaluation index factor to the safety risk evaluation set to obtain a fuzzy evaluation matrix, this approach can handle complex, fuzzy, and difficult-to-precisely quantify safety influencing factors. Performing a composite operation on the target weight set and the fuzzy evaluation matrix yields a fuzzy comprehensive evaluation set, which is then used to determine the target safety risk level. This approach can provide accurate and scientific safety evaluation results, enable timely discovery and resolution of safety hazards, and ensure the safe operation of penstocks in hydropower stations, thus improving the accuracy of penstock safety evaluations. 2. The construction of a hierarchical structure model can systematically and comprehensively sort out the factors affecting the safety of the penstock throughout its life cycle. Starting from the overall goal, it can be refined into the primary factors and their corresponding influencing factors at each stage, laying the foundation for the subsequent determination of the weights of evaluation index factors and evaluation, making the safety evaluation more targeted and accurate. It can solve the problem that existing technologies lack systematicity and comprehensiveness and ignore the dynamic changes of the entire life cycle; 3. It can assign reasonable weights to multiple safety-influencing evaluation index factors throughout the life cycle of hydropower station penstocks, thereby more scientifically and accurately considering the impact of various factors on the safety risk of penstocks, making subsequent safety evaluation results more accurate and reliable. This solves the problem that existing technologies are difficult to quantify and evaluate complex, ambiguous, and dynamically changing safety factors, and can promptly discover and address safety hazards. 4. Ensure the logical rationality and reliability of the judgment matrix by performing consistency test on the first judgment matrix and calculating the consistency ratio; when the consistency ratio does not meet the requirements, adjust the scale value of the first judgment matrix to make the weight distribution of the first-level factors more scientific and objective, thereby ensuring the accuracy of the target safety risk level determined by the full life cycle safety assessment method. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a flow chart of a full life cycle safety assessment method provided in an embodiment of the present application; Figure 2 This is a flowchart of an implementation method for evaluating a hydropower station penstock provided in an embodiment of the present application; Figure 3 This is a structural block diagram of a full life cycle safety assessment system provided by an embodiment of the present application; Figure 4 This is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application.

[0033] Description of reference numerals: 400 - electronic device; 401 - processor; 402 - communication bus; 403 - user interface; 404 - network interface; 405 - memory. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0035] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "for example" or "for instance" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "for example" or "for instance" is intended to present the relevant concepts in a concrete manner.

[0036] In the description of the embodiments of the present application, the term "plurality" means two or more. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of such features. The terms "include," "comprise," "have" and their variations all mean "including but not limited to," unless otherwise specifically emphasized.

[0037] This application provides a full life cycle safety assessment method for hydropower station penstocks, referring to Figure 1 , Figure 1 This is a flow chart of a full life cycle safety assessment method provided in an embodiment of the present application, which includes: Step S101: constructing a safety risk assessment index factor set and a safety risk evaluation set for the penstock, wherein the safety risk assessment index factor set includes multiple evaluation index factors that affect the safety of the penstock throughout its life cycle, and the safety risk evaluation set includes multiple safety risk levels throughout the life cycle of the penstock; Step S102: determining the weight of each evaluation index factor in the security risk evaluation index factor set based on the hierarchical analysis method to obtain a target weight set, and calculating the membership degree of each evaluation index factor to the security risk comment set using the fuzzy comprehensive evaluation method to generate a fuzzy evaluation matrix; Step S103, performing a composite operation on the target weight set and the fuzzy evaluation matrix to obtain a fuzzy comprehensive evaluation set; Step S104, determining the target safety risk level of the penstock according to the fuzzy comprehensive evaluation set.

[0038] Through the above steps, the safety risk evaluation index factor set of multiple evaluation index factors affecting the safety of the penstock in the whole life cycle and the safety risk comment set of multiple safety risk levels are constructed, the safety influence factors dynamically changing in the whole life cycle of the penstock can be comprehensively considered; the weights of the evaluation index factors are determined by the analytic hierarchy process to obtain a target weight set, the membership degrees of the evaluation index factors to the safety risk comment set are calculated by the fuzzy comprehensive evaluation method to obtain a fuzzy evaluation matrix, the safety influence factors which are complex, fuzzy and difficult to be accurately quantified can be processed; the target weight set and the fuzzy evaluation matrix are subjected to a composite operation to obtain a fuzzy comprehensive evaluation set, the target safety risk level is determined according to the fuzzy comprehensive evaluation, an accurate and scientific safety evaluation result can be provided, the safety hidden danger can be found and processed in time, the safe operation of the penstock of the hydropower station is ensured, and the effect of improving the accuracy of the safety evaluation of the penstock is achieved.

[0039] This embodiment combines the analytic hierarchy process (AHP) and the fuzzy comprehensive evaluation method (FCE) to conduct a comprehensive and systematic evaluation of the safety risks of the pressure steel pipe. The specific principles are as follows: construct an evaluation index system. First, a safety risk evaluation index factor set and a safety risk evaluation set for the pressure steel pipe are constructed. The evaluation index factor set covers multiple factors that affect the safety of the pressure steel pipe throughout its life cycle, such as structural design rationality, manufacturing quality, installation process, weld deformation and damage, etc. The safety risk evaluation set defines the possible safety risk levels of the pressure steel pipe, such as three levels of safety, basic safety and unsafe, or low risk, medium risk and high risk; determine the weight, and use the analytic hierarchy process to determine the weight of each evaluation index factor. The analytic hierarchy process is a method that decomposes a complex problem into multiple levels and factors, and calculates the relative importance weight of each factor by constructing a judgment matrix. Through expert scoring and other methods, each evaluation index factor is compared pairwise to form a judgment matrix, and then the weight of each factor is calculated to obtain a target weight set. The weight reflects the importance of each influencing factor in the overall safety evaluation; fuzzy comprehensive evaluation , the fuzzy comprehensive evaluation method is used to calculate the membership of each evaluation index factor to the safety risk comment set, and generate a fuzzy evaluation matrix. Among them, the fuzzy comprehensive evaluation method uses the trigonometric function membership function to calculate the membership of each evaluation index factor to different safety risk levels and maps it to the [0,1] interval. That is, for each evaluation index factor, the trigonometric function membership function is used to convert its qualitative or quantitative value into the membership of each risk level. The fuzzy comprehensive evaluation method maps the value of each evaluation index factor to the [0,1] interval through the trigonometric function membership function. In the above analysis, the degree of membership of the evaluation index factor to different safety risk levels is expressed. For example, the degree of membership of a certain evaluation index factor to the "safe" level may be 0.7, the degree of membership to the "basic safety" level may be 0.3, and the degree of membership to the "unsafe" level may be 0.0. Compound operation and result judgment: the target weight set is compounded with the fuzzy evaluation matrix to obtain a fuzzy comprehensive evaluation set. Through the fuzzy comprehensive evaluation set, the target safety risk level of the pressure steel pipe is finally determined, such as one of the three safety levels mentioned above, thereby providing a scientific basis for the safety management of the pressure steel pipe. In related technologies, it mainly relies on experience judgment and local detection, usually only focusing on a certain stage of the pressure steel pipe (such as the design or operation stage), while ignoring its dynamic changes throughout its life cycle, resulting in low accuracy of safety evaluation and difficulty in timely detection and treatment of safety hazards.This embodiment constructs an evaluation index factor set covering the entire life cycle, comprehensively considers the safety influencing factors of the penstock from design, manufacturing, installation, operation, scrapping and other stages, and realizes a systematic and comprehensive evaluation. It adopts a method that combines the hierarchical analysis method and the fuzzy comprehensive evaluation method, which can effectively handle complex, fuzzy and dynamically changing safety influencing factors, quantify the fuzzy factors, improve the scientific nature and accuracy of the safety evaluation, and provide a reliable basis for the safety management of the penstock. By accurately identifying the safety risk level of the penstock, it can timely discover potential safety hazards, take corresponding measures to deal with them in advance, reduce the risks brought by safety hazards, ensure the safe operation of the hydropower station, and improve power generation efficiency and facility safety.

[0040] In an optional embodiment, before constructing the safety risk assessment indicator factor set for the pressure steel pipe, the above method also includes: constructing a hierarchical structure model, the model includes a target layer, a criterion layer and an indicator layer, wherein the target layer is used to characterize the overall goal of the safety risk assessment of the pressure steel pipe throughout its life cycle, the criterion layer includes first-level factors for five stages: design, manufacturing, installation, operation, and scrapping, the indicator layer includes a safety risk assessment indicator factor set, and the safety risk assessment indicator factor set includes the influencing factors corresponding to each first-level factor.

[0041] In the above embodiment, constructing a hierarchical structure model can systematically and comprehensively sort out the factors that affect the safety of the penstock throughout its entire life cycle. Starting from the overall goal, it can be refined into the primary factors and their corresponding influencing factors at each stage, laying the foundation for the subsequent determination of the evaluation index factor weights and evaluation, making the safety evaluation more targeted and accurate, and solving the problem that the existing technology lacks systematicity and comprehensiveness and ignores the dynamic changes throughout the entire life cycle.

[0042] This embodiment optimizes the construction process of the safety risk assessment indicator factor set by constructing a hierarchical structure model. The hierarchical structure model includes a target layer, a criterion layer, and an indicator layer. The target layer defines the overall goal of the safety risk assessment of the penstock throughout its life cycle, namely, to conduct a comprehensive and systematic assessment of the safety of the penstock. The criterion layer divides the penstock life cycle into five stages: design, manufacturing, installation, operation, and scrapping. Each stage is a first-level factor used to divide the main aspects of the evaluation from a macro perspective. The indicator layer further refines each first-level factor and clarifies the specific influencing factors of each stage, namely, specific evaluation indicator factors, to form a safety risk assessment indicator factor set. These indicator factors are specific and operational evaluation indicators used to measure the safety risk of the penstock at each stage. The relationship between each level and factor is clear, which facilitates the determination of weights through the Analytic Hierarchy Process (AHP), ensuring the scientific and systematic nature of the evaluation. Through this structured modeling approach, the logical relationship and hierarchical structure between the influencing factors can be clearly divided, providing a clear data foundation and organizational framework for the subsequent determination of weights using the Analytic Hierarchy Process (AHP) and the calculation of membership using the fuzzy comprehensive evaluation method. Related technologies usually only focus on a certain stage of the pressure steel pipe (such as local inspection during the operation stage), while the hierarchical structure model clearly divides the five criterion layers into design, manufacturing, installation, operation, and scrapping, and compulsorily covers all key links of the entire life cycle to avoid security vulnerabilities caused by stage separation; through the hierarchical structure model, the key influencing factors of each stage are clarified, and the weight of each factor is determined through the hierarchical analysis method, making the selection of evaluation indicators more scientific and reasonable, avoiding the problem of arbitrary selection of evaluation indicators caused by relying on experience judgment in existing technologies.

[0043] In an optional embodiment, the first-level factors include the design stage, manufacturing stage, installation stage, operation stage and scrapping stage; among them, the influencing factors corresponding to the design stage include: structural design rationality, material and wall thickness selection, stress distribution and concentration, pipeline strength; the influencing factors corresponding to the manufacturing stage include: manufacturing process, production environment, and manufacturing quality; the influencing factors corresponding to the installation stage include: installation process, installation docking quality, and installation weld quality; the influencing factors corresponding to the operation stage include: operation stability, corrosion mechanism damage, concrete structure damage, weld deformation and damage, on-site monitoring and maintenance, and pipeline damage; the influencing factors corresponding to the scrapping stage include: safety assessment, safety margin, and scrapping standards.

[0044] In the above embodiment, the primary factors and their corresponding influencing factors at different stages of the penstock's life cycle are clarified, and a more complete set of safety risk assessment indicator factors is constructed. This takes into account the safety influencing factors of all aspects of the penstock's entire process from design to scrapping, making the evaluation more systematic and comprehensive, and enabling a more accurate assessment of the safety risks of the penstock throughout its life cycle.

[0045] Based on the established hierarchical structure model, this embodiment further refines and clarifies the specific secondary or tertiary evaluation influencing factors corresponding to each primary factor (i.e., design, manufacturing, installation, operation, and scrapping stages), i.e., specific evaluation index factors, thereby constructing a complete safety risk assessment index system with practical engineering significance; the selection of these influencing factors is based on engineering practice experience and theoretical analysis, covering the key points that may affect the safety of the pressure steel pipe throughout its life cycle, for example: the design stage focuses on structural rationality, material selection, stress distribution, etc.; the manufacturing stage emphasizes process control, environmental conditions and quality assurance; the installation stage focuses on installation technology, welding quality, etc.; the operation stage considers dynamic changes in long-term use such as corrosion, deformation, monitoring and maintenance; the scrapping stage focuses on safety assessment and standard implementation before decommissioning, etc. These specific influencing factors provide a clear data input basis for the subsequent use of the analytic hierarchy process (AHP) to determine weights and the fuzzy comprehensive evaluation method to calculate membership. The refined influencing factors provide a clear object for safety evaluation, making the evaluation process more targeted. The refined evaluation index system has strong universality. It is not only suitable for the safety evaluation of penstocks of hydropower stations of different sizes and types, but also can provide reference and reference for the safety management of other similar engineering structures, and promote the standardization and scientific development of industry safety evaluation standards.

[0046] In an optional embodiment, the weights of each evaluation index factor in the safety risk evaluation index factor set are determined based on the hierarchical analysis method to obtain a target weight set, including: constructing a first judgment matrix of the criterion layer using the nine-level scaling method; determining the weights of each first-level factor based on the first judgment matrix to obtain a first weight vector; constructing a judgment matrix of the index layer using the nine-level scaling method, the judgment matrix of the index layer includes multiple second judgment matrices, wherein each first-level factor corresponds to a second judgment matrix; determining the local weights of each influencing factor included in each first-level factor based on the multiple second judgment matrices to obtain multiple second weight vectors; obtaining a target weight set based on the first weight vector and the multiple second weight vectors, wherein the target weight set includes the global weights of each influencing factor in the safety risk evaluation index factor set in the full life cycle safety evaluation.

[0047] In the above embodiment, it is possible to assign reasonable weights to multiple evaluation index factors that affect the safety of the hydropower station penstock throughout its entire life cycle, thereby more scientifically and accurately considering the degree of influence of various factors on the safety risk of the penstock, making subsequent safety evaluation results more accurate and reliable, and solving the problem that the existing technology is difficult to quantify and evaluate complex, ambiguous and dynamically changing safety influencing factors, and can timely discover and deal with safety hazards.

[0048] Using the nine-level scaling method, experts or empirical data are used to compare the importance of the five first-level factors (design, manufacturing, installation, operation, and scrapping) in pairs, and a first judgment matrix is ​​constructed, that is, the first judgment matrix of the criterion layer is constructed. By normalizing and checking the consistency of the first judgment matrix, a first weight vector is obtained, which represents the relative importance of each first-level factor in the entire evaluation system. Then, for each first-level factor, a second judgment matrix is ​​constructed to reflect the relative importance of the specific influencing factors contained therein (such as the aforementioned evaluation index factors). The nine-level scaling method is also used for pairwise comparison, and the local weight vector corresponding to each second judgment matrix is ​​calculated. The local weight vector reflects the weight of each evaluation index factor in the corresponding first-level factor. The first weight vector is then weighted and synthesized with each second weight vector to obtain the global weight set (target weight set) of all influencing factors in the full life cycle safety assessment. These weights reflect the comprehensive influence of each specific influencing factor in the entire evaluation system. This embodiment structures complex problems and conducts decision analysis through a combination of qualitative and quantitative methods. By adopting the nine-level scaling method and the hierarchical analysis method, weights are determined based on expert scoring and relative comparison, making the weight distribution more scientific and reasonable, reducing subjectivity, and improving the reliability of the evaluation results. The hierarchical analysis method decomposes complex multi-factor decision-making problems into multiple levels and factors. By constructing a judgment matrix and calculating weights, it systematically handles multi-factor decision-making problems, improving the scientificity and accuracy of the evaluation. By separately calculating the criterion layer weight and the indicator layer weight, and combining the two to obtain the global weight, a hierarchical weight calculation method is implemented, ensuring the rationality of the weight distribution and making the evaluation results more convincing. This embodiment calculates and integrates weights in layers, which can accurately reflect the importance of each factor in the entire life cycle and avoid evaluation bias caused by unreasonable weights.

[0049] In an optional embodiment, a target weight set is obtained based on a first weight vector and multiple second weight vectors, including: the first weight vector is W = [W1, W2, W3, W4, W5], the i-th second weight vector is Qi = [Qi1, ..., Qim], where 1≤i≤5, Wi represents the weight of the i-th first-level factor, Qi represents the second weight vector of multiple influencing factors corresponding to the i-th first-level factor in the criterion layer; the global weight of each influencing factor contained in the i-th first-level factor is calculated according to the following formula: aik = Wi × Qik, aik represents all weights of the k-th influencing factor contained in the i-th first-level factor, m represents the number of influencing factors included in the i-th first-level factor, 1≤k≤m.

[0050] In the above embodiment, the weight of the first-level factor and the local weights of the multiple influencing factors included in each first-level factor are combined to accurately calculate the global weight of each influencing factor in the full life cycle safety evaluation, making the weight distribution of each influencing factor in the full life cycle safety evaluation of the pressure steel pipe more scientific and reasonable, which helps to improve the accuracy of the safety evaluation results.

[0051] This embodiment constructs a judgment matrix using a nine-level scaling method to obtain a first weight vector W at the criterion level and multiple second weight vectors Qi at the indicator level. The first weight vector W reflects the relative importance of the five first-level factors (design, manufacturing, installation, operation, and scrapping) in the full life cycle safety assessment. The second weight vector Qi reflects the local weight of each specific influencing factor within each first-level factor. Using the formula aik = Wi × Qik, the weight Wi of each first-level factor in the criterion level is multiplied by the local weight Qik of each influencing factor in the corresponding indicator level. The logic of this formula is that the global weight of each specific influencing factor depends not only on its importance within the corresponding stage (Qik) but also on the weight of that stage throughout the life cycle (Wi). Through this multiplication, the weights calculated in each layer are organically integrated to obtain the global weight aik of each influencing factor in the full life cycle safety assessment, thereby forming a complete target weight set. For example, the weights of the first-level indicators at the criterion level are calculated, such as the weight W1 for the design stage and the weight W4 for the operation stage. The weights of the second-level indicators within each stage are calculated, such as the local weight Q42 for corrosion mechanism damage during the operation stage. The global weight of the second-level indicator is the product of the weight of the stage in which it is located and the weight within its own stage. For example, the global weight of corrosion mechanism damage during the operation stage is W4 × Q42. Related technologies often lack clear weight integration methods when performing multi-factor weight analysis, making it impossible to clarify the mathematical relationship between the weights of factors at each level. Furthermore, related technologies do not fully consider the hierarchical relationship between the criterion level and the indicator level. The weight calculations at each level are relatively independent, failing to reflect the true contribution of lower-level factors to higher-level objectives. This embodiment uses a scientific weight integration approach to make the lifecycle safety assessment more systematic and logical. By organically combining the weights of each level, it avoids evaluation bias caused by improper weight allocation, provides reliable support for accurately determining the safety risk level of penstocks, and makes the evaluation results more consistent with engineering practice.

[0052] In an optional embodiment, the weights of each first-level factor are determined according to the first judgment matrix to obtain a first weight vector, including: normalizing the first judgment matrix by column to obtain a processed judgment matrix; averaging the elements in each row of the processed judgment matrix to obtain an initial weight vector, wherein the initial weight vector includes the initial weights of each first-level factor, and each row of elements corresponds to a first-level factor; if the consistency check of the first judgment matrix passes, the initial weight vector is determined as the first weight vector.

[0053] In the above embodiment, the first judgment matrix is ​​first normalized by columns and the average of the elements in each row is calculated to obtain an initial weight vector, and then a consistency test is performed to ensure that the first judgment matrix is ​​reasonable, and finally the first weight vector of the first-level factor is determined, so that the determination of the first-level factor weight is more scientific, reasonable and reliable, thereby improving the accuracy of the life cycle safety assessment method in judging the safety risk level of the hydropower station penstock.

[0054] The first judgment matrix (criterion layer judgment matrix) is normalized by column. Normalization is to divide each column element of the first judgment matrix by the sum of the column so that the sum of each column is 1. The normalized matrix is ​​called the processed judgment matrix (or the normalized judgment matrix). The elements of each row in the normalized judgment matrix are averaged to obtain the initial weight vector. Each element in the initial weight vector represents the initial weight of the corresponding first-level factor. In the hierarchical analysis method, the construction of the first judgment matrix may be subjective, so a consistency test is required. The purpose of the consistency test is to ensure that the construction of the first judgment matrix is ​​sufficiently reasonable. If the consistency test passes, it is considered that the construction of the first judgment matrix is ​​reasonable, and the initial weight vector can be used as the final weight vector (i.e., the first weight vector). Through normalization and consistency testing, the scientificity and rationality of the weight calculation are ensured. Normalization makes the weight calculation more fair, and the consistency test avoids the irrationality caused by subjective judgment.

[0055] Similarly, for the aforementioned multiple second judgment matrices, a similar method as described above can be adopted to obtain the corresponding second weight vectors.

[0056] In an optional embodiment, the consistency check includes calculating a consistency ratio CR, and when CR is less than 0.1, the first judgment matrix is ​​judged to have passed the consistency check; wherein the specific steps of the consistency check include: calculating the maximum eigenvalue λ of the first judgment matrix ax And consistency index CI=(λ ax -n) / (n-1), where n represents the number of first-level factors in the criterion layer, A represents the first judgment matrix, W represents the initial weight vector, and Wi represents the weight corresponding to the i-th first-level factor; the random consistency index RI corresponding to n is obtained by looking up the table, and the consistency ratio CR = CI / RI is calculated; if CR ≥ 0.1, the scale value of the first judgment matrix is ​​adjusted until CR < 0.1; if CR < 0.1, the first judgment matrix is ​​judged to have passed the consistency test.

[0057] In the above embodiment, in the process of determining the weights of the first-level factors after constructing the hierarchical structure model, the first judgment matrix is ​​subjected to consistency testing and the consistency ratio is calculated to ensure the logical rationality and reliability of the judgment matrix; when the consistency ratio does not meet the requirements, the scale value of the first judgment matrix is ​​adjusted to make the weight distribution of the first-level factors more scientific and objective, thereby ensuring the accuracy of the full life cycle safety assessment method in determining the target safety risk level.

[0058] Calculate the maximum characteristic root λmax of the first judgment matrix, and according to the formula CI=(λ ax -n) / (n-1) calculates the consistency index, where n is the number of first-level factors in the criterion layer, such as n=5. Based on the number of first-level factors n in the criterion layer, the corresponding random consistency index (RI) is retrieved from the standard table, and the consistency ratio CR is calculated. If CR<0.1, the first judgment matrix passes the consistency test and the construction of the first judgment matrix is ​​considered reasonable. If CR≥0.1, the scale value of the first judgment matrix needs to be adjusted and CR recalculated until CR<0.1. Consistency testing is an important step in the hierarchical analysis method, used to verify the rationality of the judgment matrix. By calculating CR and determining whether it is less than 0.1, it can ensure that the construction of the judgment matrix is ​​sufficiently rational and avoid irrationality caused by subjective judgment.

[0059] In an optional embodiment, determining the target safety risk level of the penstock according to the fuzzy comprehensive evaluation set includes: determining the safety risk level corresponding to the maximum value in the fuzzy comprehensive evaluation set as the target safety risk level according to the maximum membership principle.

[0060] In the above embodiment, the target safety risk level of the penstock can be accurately and conveniently determined based on the fuzzy comprehensive evaluation set, thereby improving the scientificity and accuracy of the life cycle safety evaluation method in determining the safety risk level.

[0061] The target safety risk level of the pressure steel pipe can be accurately and conveniently determined based on the fuzzy comprehensive evaluation set, which improves the scientificity and accuracy of the full life cycle safety assessment method in determining the safety risk level. In the fuzzy comprehensive evaluation set, the safety risk level corresponding to the maximum membership value is selected as the target safety risk level. For example, if the fuzzy comprehensive evaluation set is [0.2, 0.5, 0.3], which corresponds to "safe", "basic safety" and "unsafe" respectively, then the maximum membership value is 0.5, and the corresponding "basic safety" is the target safety risk level.

[0062] In an optional embodiment, the indicator layer includes a dynamic update mechanism to iteratively modify the fuzzy membership function and weight parameters based on historical data.

[0063] In the above embodiment, the hierarchical structure model is constructed to make the safety evaluation more systematic, and the multiple evaluation index factors affecting the safety in the whole life cycle are considered to make the evaluation more comprehensive. The combination of the analytic hierarchy process and the fuzzy comprehensive evaluation method can process complex and fuzzy safety influencing factors and obtain the membership degree and weight, and the fuzzy comprehensive evaluation set is obtained through the compound operation to determine the target safety risk level. The dynamic updating mechanism of the index layer can iteratively correct the fuzzy membership function and the weight parameter according to the historical data, so that the safety evaluation can adapt to the dynamic changes in the whole life cycle of the penstock, and the accuracy and scientificity of the evaluation result are improved.

[0064] The index layer is a specific factor set of the safety evaluation system. Historical data (such as stress monitoring data and corrosion rate data in the operation stage, quality detection records in the manufacturing stage, etc.) are collected regularly or at a specific event trigger (such as penstock maintenance and major environmental changes) through preset rules or algorithms. The historical data reflects the real state distribution of each evaluation index factor in the actual scene. By analyzing these data, the parameters of the triangular function membership function (such as the peak value and interval range of the function) are adjusted to make the membership degree calculation more in line with the actual situation. For example, if the operation data shows that the corrosion rate of a certain type of penstock increases in a specific environment, the membership function of the “corrosion mechanism damage” factor can be adjusted to increase the membership degree calculation weight of the unsafe level (or high risk level). Using the safety event records and risk assessment results in the historical data, combined with the logic of the analytic hierarchy process, the relative importance of each factor is re-evaluated, and the weight vectors of the criterion layer and the index layer are adjusted. For example, if a hydropower station has caused multiple safety accidents due to the quality of the installed welds, the weight of the “weld quality” factor in the installation stage and even the whole life cycle evaluation can be increased through historical data.

[0065] In an optional embodiment, the above method further comprises: the fuzzy evaluation matrix and the fuzzy comprehensive evaluation set are dynamically updated according to real-time monitoring data, specifically including: periodically collecting target operation data in the operation stage; recalculating the membership degree of the corresponding evaluation index factor based on the target operation data to obtain an updated fuzzy evaluation matrix; updating the fuzzy comprehensive evaluation set according to the updated fuzzy evaluation matrix, and outputting the current safety level.

[0066] In the above embodiment, the fuzzy evaluation matrix and the fuzzy comprehensive evaluation set can be updated regularly based on the target operation data in the operation stage to realize real-time evaluation of the target safety risk level of the penstock, timely reflect the dynamic changes of the penstock in the operation process, improve the accuracy and timeliness of the safety evaluation result, and enable safety hazards to be discovered and handled in a timely manner.

[0067] This embodiment dynamically updates key fuzzy evaluation parameters by collecting real-time data during the operation phase. During the penstock operation phase, target operation data is regularly collected, including but not limited to corrosion damage, weld deformation, and damage. This data reflects the current operating status of the penstock and real-time changes in safety influencing factors. Based on the collected target operation data, the trigonometric membership function is used to recalculate the membership of each evaluation index factor to different safety risk levels. For example, if the stress value at a certain point in the pipeline exceeds a threshold, the membership of the "stress distribution and concentration" factor to the "unsafe" (or "high risk") level is correspondingly increased, thereby forming an updated fuzzy evaluation matrix. The updated fuzzy evaluation matrix is ​​then combined with a fixed target weight set for a composite operation (such as weighted average) to recalculate an updated fuzzy comprehensive evaluation set. This updated fuzzy comprehensive evaluation set comprehensively reflects the safety risk status of the penstock under the current operation data. Ultimately, the current safety level is output according to the maximum membership principle, achieving real-time updating of the evaluation results. This embodiment dynamically updates evaluation results using real-time monitoring data, enabling rapid identification of abnormalities in penstock operation and outputting safety levels. For example, a high-risk warning can be immediately issued when pipeline stress suddenly changes. Compared to traditional periodic inspections, risk response time is significantly shortened, saving valuable time for emergency response. Recalculating membership and updating evaluation sets based on real-time data ensures that evaluation results are more closely aligned with the penstock's actual operating status. The dynamic update mechanism, combined with real-time monitoring data, lays the foundation for intelligent, digital management of hydropower station penstocks. By integrating IoT devices and data analysis systems, automated safety evaluations can be achieved, driving the industry toward intelligent operations and maintenance.

[0068] In an optional embodiment, the security risk evaluation set includes: a security level, a basic security level, and an unsafe level.

[0069] In the above embodiment, the safety risk level classification of the penstock throughout its life cycle is clarified, which facilitates a more detailed and accurate assessment and judgment of the safety status of the penstock.

[0070] The safety risk status of the pressure steel pipe is divided into three levels: "safety level", "basic safety level" and "unsafe level". The safety level indicates that the pressure steel pipe is in a very ideal state in the current state, has no obvious safety hazards, and can operate normally; the basic safety level means that although there are some minor problems or potential risks, these problems are not enough to immediately threaten the safety of the system and require regular inspection and monitoring; the unsafe level indicates that there are serious safety hazards, which may affect the normal operation of the system or even cause accidents, and immediate measures must be taken to repair or replace it.

[0071] In an optional embodiment, the above method further includes: when the target security risk level is a basic security level, outputting a list of specific indicators that need to be maintained; when the target security risk level is an unsafe level, triggering an alarm.

[0072] In the above embodiment, when the target safety risk level is the basic safety level, a list of specific indicators that need to be maintained is output, which allows staff to perform targeted maintenance on the penstock and eliminate potential safety hazards in a timely manner; when the target safety risk level is an unsafe level, an alarm is triggered, which can promptly remind staff to take measures to reduce the probability of safety accidents and ensure the safe operation of the penstock of the hydropower station.

[0073] When the target safety risk level is "basic safety level", it indicates that there are potential hidden dangers in the pressure steel pipe but it does not affect the operation for the time being. At this time, the system automatically outputs a list of specific indicators that need to be maintained. The content of the list is based on the risk indicators with higher membership in the fuzzy comprehensive evaluation (such as "corrosion mechanism damage", "weld deformation", etc.), and clarifies the operation and maintenance priority; when the level is "unsafe level", it indicates that the risk has exceeded the safety threshold. The system immediately triggers the alarm mechanism and sends emergency warnings to the operation and maintenance personnel through sound and light signals, SMS notifications, etc., forcibly interrupting the dangerous operation state.

[0074] Obviously, the above-described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The present application will be described in detail below with reference to specific embodiments.

[0075] The embodiment of the present application provides a method for evaluating the safety of water diversion penstocks in hydropower stations. The safety level of penstocks in hydropower stations throughout their entire life cycle involves multi-level and multi-fuzzy influencing factors such as design, manufacturing, installation, operation, maintenance, and scrapping. The analytic hierarchy process-fuzzy synthesis method is used to deal with complex system problems with multiple factors, fuzziness, and uncertainty. According to the safety issues of penstocks at different stages, it is decomposed into the target layer, the criterion layer, and the indicator layer. Through the AHP-FCE coupling model, the complex safety issues are transformed into a calculable and reproducible quantitative process, so that the safety of penstocks can be evaluated more scientifically.

[0076] In view of the multi-source heterogeneity, fuzziness and dynamic evolution characteristics of the life cycle safety assessment of hydropower station penstocks, the core idea is to decompose the life cycle safety assessment problem of penstocks into a quantifiable multi-level indicator system by building a hierarchical structure model, and use a combination of qualitative and quantitative methods to achieve accurate expression of fuzzy problems. The specific process is as follows Figure 2 Shown, including: S201, define the set of safety risk indicators for the entire life cycle; S202, classify risk assessment levels, such as safe, basically safe, and unsafe; S203, using the analytic hierarchy process to determine the weight of each factor, and constructing the impact factor scale using the "nine-level scaling method"; S204, constructing a judgment matrix of the criterion layer and the indicator layer; S205, calculating the weight vector and performing consistency check; S206, determining whether the consistency check passes; When the judgment result of the above step S206 is no, return to step S204; when the judgment result of the above step S206 is yes, go to step S207; S207, using fuzzy comprehensive method to calculate the membership degree of each index value; S208, quantitatively constructing the evaluation matrix of each single factor subset to obtain a fuzzy matrix; S209, combining the weight set and the fuzzy matrix to perform a composite operation; S210: Determine the final comment set according to the maximum membership principle to obtain the final security risk level.

[0077] The present embodiment is described in detail below: Step 1: Define the safety risk assessment index factor set for the entire life cycle of the penstock. U=[U1,U2,...,U N ] is the first-level factor set (corresponding to the aforementioned first-level factors), U n =[u n1 ,u n2 ,...,u ni ] is the second-level factor set (corresponding to the aforementioned security risk assessment indicator factor set), u ni It represents the i-th factor under the n-th factor of the first layer, n=1, 2, ..., N; i=1, 2, ..., m, m represents the number of influencing factors contained in the n-th factor of the first layer, and the m value corresponding to different first-layer factors (i.e., first-level factors) may be different.

[0078] For example, if we select 5 first-level indicators of the criterion layer (design, manufacturing, installation, operation, and scrapping), then the first-level factor set U = [design U1, manufacturing U2, installation U3, operation U4, scrapping U5]; Select the secondary indicators of the indicator layer: Design the four factors in the U1 stage (structural design rationality, material and wall thickness selection, stress distribution and concentration, pipeline strength), then U1=[u 11 ,u 12 ,u 13 ,u 14 ]; The three factors in the manufacturing U2 stage (manufacturing process, production environment, and manufacturing quality) are as follows: U2 = [u21 ,u 22 ,u 23 ]; The three factors of the installation U3 stage (installation process, installation docking quality, installation weld quality) are as follows: U3=[u 31 ,u 32 ,u 33 ]; six factors in the U4 stage of operation (operation stability, corrosion mechanism damage, concrete structure damage, weld deformation and damage, on-site monitoring and maintenance, pipeline damage), U4 = [u 41 ,u 42 ,u 43 ,u 44 ,u 45 ,u 46 ]; The three factors of scrapping stage U5 (safety assessment, safety margin, scrapping standard), U5 = [u 51 ,u 52 ,u 53 ].

[0079] Step 2: The impact degree of safety risk of penstock throughout its life cycle is divided into different levels, namely V = [v1, v2..., v j ]; For example, the safety risk level of a penstock throughout its lifecycle can be divided into three levels: safe, basically safe, and unsafe, i.e., V = [v1, v2, v3]. Three corresponding criteria are defined: v1: safe, no measures required; v2: basically safe, safety requirements are largely met, but relevant measures are required; and v3: unsafe, requiring remedial measures or scrapping and replacement to ensure safe operation. In practical applications, more levels can be used as needed.

[0080] Step 3: Use the analytic hierarchy process to determine the factors u i The weight a i , the "nine-level scaling method" is used to construct the impact factor scale, construct the comparison matrix of each layer to the previous layer, and establish the weight set, A = [a1, a2, ..., a i ]; using the "nine-level scale method", as shown in Table 1: Table 1 Step 4: Each judgment matrix is ​​multiplied by the corresponding indicator weight vector and normalized to obtain a fuzzy comprehensive evaluation set. The judgment matrix for constructing the criterion layer is as follows, and the judgment matrix for constructing the indicator layer is similar.

[0081] Step 5: For each judgment matrix (including the judgment matrix at the criterion level and the judgment matrices at the indicator level), we need to perform a consistency test and calculate the consistency index CI and consistency ratio CR to test their consistency. If the test passes, the data is acceptable. If the test fails, we need to return and recalculate the data. For example, we can construct the judgment matrix at the criterion level according to step 4. The specific operations are as follows: 1. Calculate the weight vector W (corresponding to the first weight vector mentioned above), normalize each column, and then find the row average.

[0082] Averaging the column items, the first column is 1+1 / 3+1 / 2+2+1 / 2=4.33, the second column is 3+1+1+3+2=10, the third column is 9, the fourth column is 2.42, and the fifth column is 8.

[0083] Normalization: The calculation results are approximately: The average row weight W is obtained: W = [0.24, 0.10, 0.11, 0.40, 0.15].

[0084] 2. Calculate the maximum eigenvalue

[0085] Calculate A*W: First row: 1×0.24+3×0.10+2×0.11+1 / 2×0.40+3×0.15 (same for the second to fifth rows), A*W = [1.25, 0.49, 0.53, 2.11, 0.78]; calculate Then take the average value λ max =(5.18+5.06+5.07+5.25+5.10) / 5=5.13.

[0086] 3. Use consistency test formula

[0087] Perform the test according to the consistency test table (such as Table 2).

[0088] Table 2 n 1 2 3 4 5 RI 0 0 0.52 0.89 1.12 If the test passes, the data is feasible.

[0089] It should be noted that the above steps 4 and 5 are further refinements of step 3.

[0090] Step 6: Use fuzzy comprehensive evaluation method to calculate the membership of each index value to different standard value ranges, and map each element in the set to the interval [0, 1]; For example, the impact of each single factor (secondary indicator) on the entire life cycle is evaluated, and the membership of the trigonometric function risk level is used to map each element in the set to the interval [0, 1]: Step 7: For each single factor u in the factor set i The whole life cycle impact degree is evaluated and the single factor fuzzy evaluation subset R is obtained. i , and then construct each single factor subset into a fuzzy evaluation matrix R; For example, through quantitative data construction of the evaluation matrix of each single factor subset, assuming that the "pipeline strength" indicator in the design stage is evaluated, the quantitative indicator is: the measured value of pipeline strength X (unit: MPa), and the design requirement minimum value is 100 MPa. Set the threshold points, x1 (unsafe limit), x2 (basic safety lower limit), x3 (safe lower limit). Comment set: safety V1: (y ≥ x3), basic safety V2: (x1 < y < x3), unsafe V3: (y ≤ x1). If the measured value of pipeline strength X = 85 MPa, set x1 = 80, x2 = 90, x3 = 100, then according to the trigonometric function membership calculation, we get: Then the single factor indicator is mapped to the interval [0, 1] r1 = (0.5, 0.5, 0), and the same applies to other indicators.

[0091] Step 8: In order to comprehensively evaluate the impact of all factors on the life cycle of penstock, the weight set A and the fuzzy matrix R are combined for composite operation to construct the fuzzy comprehensive evaluation set B. For example, the weight set A determined by AHP is a 1×19 matrix, and the fuzzy mathematics matrix R is a 19×3 matrix. After performing compound operations on them, the fuzzy comprehensive evaluation set B of the entire life cycle of the penstock is obtained.

[0092] B=A*R=[0.185, 0.474, 0.341].

[0093] Step 9: Finally, according to the principle of maximum membership, the maximum value in the fuzzy comprehensive evaluation set is taken as the corresponding comment level.

[0094] For example: Based on the maximum membership principle, max(b i )=V2=0.474, take the maximum value in B as the corresponding evaluation level, and determine the final safety status as basic safety.

[0095] In the above embodiment, the weight of each factor is determined using the analytic hierarchy process (AHP). A comparison matrix is ​​first constructed for each layer relative to each factor in the previous layer (using a nine-level scaling method). The weight vector is calculated using the constructed matrix to obtain a set of weight vectors. Then, based on fuzzy mathematics, the degree of membership of each indicator value to different standard value ranges is calculated, indicating the degree to which the element belongs to the set. Determining the degree of membership transforms the qualitative evaluation of the many factors affecting the life cycle of the pressure steel pipe into a quantitative evaluation. The many influencing factors in the evaluation system include both qualitative and quantitative indicators, and the grading standards and units of various indicators vary, making comparison and evaluation difficult. Therefore, for uniformity, actual data from safety tests are used for indicators that are easy to quantify. For indicators that are difficult to quantify (such as manufacturing process and installation quality), the results of actual data review are used (such as querying the process flow during manufacturing, docking accuracy during installation, and measurement results). Finally, the scores are assigned based on engineering experience, expert consultation, and existing research results. The membership of all influencing factors is determined based on measured data (such as stress detection data, corrosion detection data, concrete detection data, weld detection data, etc.) and actual reference materials, engineering experience, expert consultation scores, and existing research results (such as the comparison between measured stress detection data and design, the safety margin, and whether it is safe, basically safe, or unsafe). The membership is finally mapped to the [0, 1] interval through formula calculation. A composite operation is performed based on the weight set matrix determined by AHP and the single factor matrix of the fuzzy mathematical matrix to obtain the fuzzy comprehensive evaluation set for the entire life cycle of the penstock.

[0096] The present application also provides a full life cycle safety assessment system for executing the full life cycle safety assessment method of any of the above embodiments, such as Figure 3 As shown, Figure 3 This is a structural block diagram of a full life cycle safety assessment system provided in an embodiment of the present application, which includes: A construction module 31 is used to construct a safety risk assessment indicator factor set and a safety risk evaluation set for the penstock, wherein the safety risk assessment indicator factor set includes multiple evaluation indicator factors that affect the safety of the penstock throughout its life cycle, and the safety risk evaluation set includes multiple safety risk levels throughout the life cycle of the penstock; Processing module 32 is used to determine the weight of each evaluation index factor in the security risk evaluation index factor set based on the hierarchical analysis method to obtain a target weight set, and to calculate the membership degree of each evaluation index factor to the security risk comment set using the fuzzy comprehensive evaluation method to generate a fuzzy evaluation matrix; The operation module 33 is used to perform a composite operation on the target weight set and the fuzzy evaluation matrix to obtain a fuzzy comprehensive evaluation set; the determination module 34 is used to determine the target safety risk level of the penstock according to the fuzzy comprehensive evaluation set.

[0097] It should be noted that the above embodiments provide systems that implement their functions using only the division of the above functional modules as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0098] The present application also provides a computer-readable storage medium, which stores instructions. When the instructions are executed, any one of the above-mentioned method steps is executed.

[0099] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk, or an optical disk.

[0100] This application also discloses an electronic device. Figure 4 As shown, Figure 4 4 is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present application. The electronic device 400 may include: at least one processor 401, at least one communication bus 402, a user interface 403, at least one network interface 404, and a memory 405.

[0101] The communication bus 402 is used to implement the connection and communication between these components.

[0102] The user interface 403 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 403 may also include a standard wired interface and a wireless interface.

[0103] The network interface 404 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0104] The processor 401 may include one or more processing cores. The processor 401 utilizes various interfaces and lines to connect the various parts of the entire electronic device (such as a server), and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 405, and calling data stored in the memory 405. Optionally, the processor 401 may be implemented in the form of at least one hardware of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 401 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU mainly processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display; and the modem is used to handle wireless communications. It is understandable that the above-mentioned modem may not be integrated into the processor 401 and may be implemented separately through a chip.

[0105] Among them, the memory 405 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 405 includes a non-transitory computer-readable storage medium. The memory 405 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 405 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 405 may optionally be at least one storage device located away from the aforementioned processor 401. Refer to Figure 4 , the memory 405 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a full life cycle safety assessment method.

[0106] exist Figure 4In the electronic device 400 shown, the user interface 403 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 401 can be used to call an application program of a full life cycle safety assessment method stored in the memory 405. When executed by one or more processors 401, the electronic device 400 executes one or more of the methods described in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should know that this application is not limited to the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0107] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0108] In the several embodiments provided in this application, it should be understood that the disclosed device or system can be implemented in other ways. For example, the device or system embodiments described above are merely schematic, such as the division of units, which is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0109] The foregoing is merely an exemplary embodiment of the present disclosure and is not intended to limit the scope of the present disclosure. In other words, any equivalent variations and modifications made in accordance with the teachings of the present disclosure are still within the scope of the present disclosure. Those skilled in the art will readily conceive of other embodiments of the present disclosure after considering the disclosure herein.

[0110] This application is intended to cover any modifications, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary technical means in the technical field not described in the present disclosure.

Claims

1. A full life cycle safety assessment method, characterized in that: Applied to hydropower station penstocks, including: Constructing a safety risk assessment index factor set and a safety risk comment set for the penstock, wherein the safety risk assessment index factor set includes multiple assessment index factors that affect the safety of the penstock throughout its life cycle, and the safety risk comment set includes multiple safety risk levels throughout its life cycle; Determining the weight of each evaluation index factor in the security risk evaluation index factor set based on the hierarchical analysis method to obtain a target weight set, and calculating the membership degree of each evaluation index factor to the security risk comment set using a fuzzy comprehensive evaluation method to generate a fuzzy evaluation matrix; Performing a composite operation on the target weight set and the fuzzy evaluation matrix to obtain a fuzzy comprehensive evaluation set; The target safety risk level of the penstock is determined based on the fuzzy comprehensive evaluation set.

2. The method according to claim 1, characterized in that Before constructing the safety risk assessment index factor set for the penstock, the method further includes: A hierarchical structure model is constructed, which includes a target layer, a criterion layer and an indicator layer, wherein the target layer is used to characterize the overall goal of the safety risk assessment of the penstock throughout its life cycle; the criterion layer includes the first-level factors of five stages, namely, design, manufacturing, installation, operation and scrapping; the indicator layer includes the safety risk assessment indicator factor set, and the safety risk assessment indicator factor set includes the influencing factors corresponding to each of the first-level factors.

3. The method according to claim 2, characterized in that The first-level factors include the design stage, manufacturing stage, installation stage, operation stage and scrapping stage; The influencing factors corresponding to the design stage include: structural design rationality, material and wall thickness selection, stress distribution and concentration, and pipeline strength; The influencing factors corresponding to the manufacturing stage include: manufacturing process, production environment, and manufacturing quality; The influencing factors corresponding to the installation stage include: installation process, installation docking quality, and installation weld quality; The influencing factors corresponding to the operation stage include: operation stability, corrosion mechanism damage, concrete structure damage, weld deformation and damage, on-site monitoring and maintenance, and pipeline damage; The influencing factors corresponding to the scrapping stage include: safety assessment, safety margin, and scrapping standards.

4. The method according to claim 2, characterized in that The weights of the various evaluation index factors in the safety risk evaluation index factor set are determined based on the hierarchical analysis method to obtain a target weight set, including: Constructing the first judgment matrix of the criterion layer by using a nine-level scaling method; Determine the weight of each of the first-level factors according to the first judgment matrix to obtain a first weight vector; A nine-level scaling method is used to construct a judgment matrix of the indicator layer, wherein the judgment matrix of the indicator layer includes a plurality of second judgment matrices, wherein each of the first-level factors corresponds to one second judgment matrix; Determining the local weight of each influencing factor included in each of the first-level factors according to the multiple second judgment matrices to obtain multiple second weight vectors; The target weight set is obtained according to the first weight vector and multiple second weight vectors, wherein the target weight set includes the global weight of each influencing factor in the safety risk assessment indicator factor set in the full life cycle safety assessment.

5. The method according to claim 4, characterized in that Determining the weight of each of the first-level factors according to the first judgment matrix to obtain a first weight vector includes: Normalizing the first judgment matrix by columns to obtain a processed judgment matrix; Performing an average calculation on each row of elements in the processed judgment matrix to obtain an initial weight vector, wherein the initial weight vector includes the initial weights of each of the first-level factors, and each row of elements corresponds to one of the first-level factors; When the consistency check of the first judgment matrix passes, the initial weight vector is determined as the first weight vector.

6. The method according to claim 5, characterized in that The consistency check includes calculating a consistency ratio CR, and when the CR is less than 0.1, it is determined that the first judgment matrix passes the consistency check; The specific steps of the consistency check include: Calculate the maximum eigenvalue λ of the first judgment matrix ax And consistency index CI=(λ ax -n) / (n-1), where n represents the number of the first-level factors in the criterion layer, A represents the first judgment matrix, W represents the initial weight vector, and Wi represents the weight corresponding to the i-th first-level factor; Look up the table to obtain the random consistency index RI corresponding to n, and calculate the consistency ratio CR=CI / RI; If CR ≥ 0.1, adjust the scale value of the judgment matrix until CR < 0.1; If CR<0.1, it is determined that the first judgment matrix passes the consistency test.

7. The method according to claim 1, characterized in that Determining the target safety risk level of the penstock according to the fuzzy comprehensive evaluation set includes: According to the maximum membership principle, the security risk level corresponding to the maximum value in the fuzzy comprehensive evaluation set is determined as the target security risk level.

8. A full life cycle safety assessment system, characterized in that: The method for performing any one of claims 1 to 7 comprises: A construction module is used to construct a safety risk evaluation index factor set and a safety risk comment set for the penstock, wherein the safety risk evaluation index factor set includes multiple evaluation index factors that affect the safety of the penstock throughout its life cycle, and the safety risk comment set includes multiple safety risk levels throughout its life cycle; a processing module for determining the weight of each evaluation index factor in the security risk evaluation index factor set based on the hierarchical analysis method to obtain a target weight set, and calculating the membership degree of each evaluation index factor to the security risk comment set using a fuzzy comprehensive evaluation method to generate a fuzzy evaluation matrix; An operation module, configured to perform a composite operation on the target weight set and the fuzzy evaluation matrix to obtain a fuzzy comprehensive evaluation set; A determination module is used to determine the target safety risk level of the penstock according to the fuzzy comprehensive evaluation set.

9. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

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