Power generation equipment comprehensive risk management method based on FMEA-Swiss cheese model

Abstract

The invention discloses a power generation equipment comprehensive risk management method based on an FMEA-Swiss cheese model. The method comprises the following steps: defining key components and process steps of a power generation system; performing FMEA analysis on each key component and process step, specifically, after the FMEA identifies a potential fault mode in each key component and process step, determining a fault reason of the potential fault mode, evaluating a fault result of the potential fault mode, and calculating an RPN of the potential fault mode; all components of the power generation system are regarded as different defense layers by utilizing a Swiss cheese model, and the mode that each fault mode identified by the FMEA passes through each defense layer is analyzed; combining the analysis of FMEA and the perspective of the defense layer of the Swiss cheese model to formulate risk mitigation measures; and making a risk management plan by using risk mitigation measures, and regularly rechecking FMEA and Swiss cheese models.

Description

Technical Field

[0001] The present invention belongs to the technical field of power generation system risk management, and in particular relates to a comprehensive risk management method for power generation equipment based on a FMEA-Swiss cheese model. Background Art

[0002] The cheese model (often referred to as the "Swiss cheese model") is a model used for risk management and safety management. It was proposed by James Reason. The core idea is to compare mistakes and failures in an organization to holes in Swiss cheese. Each piece of cheese represents a layer of defense, and the holes represent defects in the defense layer. Only when defects at multiple levels are aligned can risks pass through all the defense layers and cause accidents.

[0003] Failure Mode and Effects Analysis (FMEA) is a systematic analysis method used to identify potential failure modes in products or processes, determine the causes of these failure modes, evaluate their impact on system or product performance, and propose corresponding preventive measures or improvement suggestions. FMEA is widely used in product design, manufacturing processes, service processes, and maintenance activities to improve the reliability, safety, and quality of products or systems.

[0004] Although the Swiss cheese model provides a multi-layer defense perspective, it is still insufficient in determining which risks need to be managed first. A single equipment FMEA failure analysis tends to overlook complex risks. Currently, there is no public risk management method that combines FMEA with the Swiss cheese model. Summary of the invention

[0005] The purpose of the present invention is to overcome the problem of insufficient risk priority management when the Swiss cheese model is used alone or the problem of easy neglect of complex risks when FMEA is used alone. A comprehensive risk management method for power generation equipment based on the FMEA-Swiss cheese model is proposed. The fault analysis of FMEA is extended by the Swiss cheese model to reveal complex risks that may be neglected by a single analysis. The risk priority number RPN of FMEA and the defense layer analysis of the Swiss cheese model are combined to optimize resource allocation.

[0006] In order to achieve the above object, the present invention adopts the following technical scheme: A comprehensive risk management method for power generation equipment based on FMEA-Swiss cheese model, comprising the following steps: S1. Define the key components and process steps of the power generation system; S2. Analyze each key component and process step using FMEA. The specific analysis using FMEA is as follows: Conduct failure mode and effect analysis on power generation equipment. After identifying the potential failure mode of power generation equipment, determine the failure cause of the potential failure mode and evaluate the failure consequence of the potential failure mode, and calculate the RPN of the potential failure mode. S3. Define defense modules using the Swiss cheese model and analyze how each potential failure mode identified by FMEA passes through each defense layer; S4. Based on the analysis results of FMEA, a decision tree or logic flow chart is constructed to provide a decision path for each potential failure mode. The decision path guides the selection of defense module combinations for potential failure modes based on the RPN value of the potential failure mode. Combining the analysis of FMEA in S2 and the defense layer perspective of the Swiss cheese model in S3, risk mitigation measures are formulated. S5. Develop a risk management plan using the risk mitigation measures in S4 and review the FMEA and Swiss cheese model regularly.

[0007] Further, identifying potential failure modes of power generation equipment in S2 includes potential ways to cause system function failure; Failure causes include all causes that lead to any potential failure mode; Failure consequences include the impact of any potential failure mode on system function, safety and reliability; The calculation formula used to calculate the RPN for a potential failure mode is as follows: RPN = S × O × D Among them, RPN is the risk priority number. In the FMEA process, the evaluation parameters of each potential failure mode include S, O and D, S is the severity, O is the probability of occurrence, and D is the difficulty of detection.

[0008] Furthermore, S3 includes defining defense modules and potential failure mode analysis, building decision trees or logic flow charts, and selecting and combining modules.

[0009] Furthermore, the definition of defense modules and failure mode analysis is specifically as follows: defense modules are defined, each of which corresponds to different types of potential failure mode risk levels; the types of defense modules include basic defense, enhanced defense, and emergency response.

[0010] Furthermore, S4 is specifically as follows: based on the RPN value of each potential failure mode determined by FMEA, a decision tree or a logic flow chart is constructed, wherein the decision tree or the logic flow chart provides a decision path for each potential failure mode, and the potential failure mode selects a defense module for combination through the decision path using the RPN value of the failure mode; the logic flow chart shows the defense module adopted when the RPN value of the potential failure mode reaches a threshold.

[0011] Furthermore, the defense modules are selected for combination using the RPN value of the fault mode specifically as follows: a defense module is dynamically selected for configuration according to the current potential fault mode and its RPN value.

[0012] Furthermore, S4 is specifically as follows: identifying the defense layer defects of potential failure modes, and building cross-level preventive measures and improvement measures to repair the defense layer defects.

[0013] Furthermore, the risk management plan is a risk management plan when the power generation system technology is upgraded or the operating conditions of the power generation equipment change.

[0014] An integrated risk management system for power generation equipment based on the FMEA-Swiss cheese model, including an FMEA analysis module for defining the scope and functions of the integrated risk management system for power generation equipment, identifying potential failure modes, identifying failure causes and failure consequences, calculating RPN values, and formulating mitigation measures; Swiss cheese analysis module, used to identify defense layers, assess defense layer deficiencies, analyze interactions between deficiencies, and develop defense measures; The failure mode and defense layer module is integrated to obtain the defense strategy decision logic after integrating the mitigation measures of the FMEA analysis module and the defense measures of the Swiss cheese analysis module. The defense strategy decision logic is modularized to obtain a modular defense strategy decision logic. According to the modular defense strategy decision logic, the optimized defense measures based on RPN are obtained. The modular defense strategy decision logic includes a low-risk basic module, a medium-risk basic enhancement module, and a high-risk basic enhancement emergency module.

[0015] Furthermore, the FMEA analysis module calculates the RPN values ​​and maps them to the defense layers identified by the Swiss cheese analysis module; The logical decision process input of the FMEA analysis module and the Swiss cheese analysis module integrates the defense strategy decision logic of the failure mode and defense layer module to modularize; Integrate the RPN-based optimized defense measures of the failure mode and defense layer module to dynamically feed back the potential failure modes identified by the FMEA analysis module; The RPN-based optimized defense measures that integrate the failure mode and defense layer modules dynamically adjust the defense layers identified by the Swiss cheese analysis module.

[0016] Compared with the prior art, the present invention has the following beneficial technical effects: The present invention proposes a comprehensive risk management method for power generation equipment based on the FMEA-Swiss cheese model. By combining the Swiss Cheese Model with the Failure Mode and Effect Analysis (FMEA), compared with the single equipment FMEA failure analysis, firstly, FMEA provides in-depth risk identification by analyzing the potential failure modes of each component and process in detail. Then, this analysis is further extended through the Swiss cheese model, considering the interaction of different defense layers and the path of fault penetration, thereby revealing complex risks that may be overlooked by a single analysis. Although the Swiss cheese model provides a multi-layer defense perspective, it helps to identify and strengthen key defense layers to ensure that even if certain measures fail, other layers can prevent the spread of failures. Combining the risk priority number (RPN) of FMEA and the defense layer analysis of the Swiss cheese model can more effectively determine which risks need to be managed first, thereby optimizing resource allocation and ensuring that key risks are properly handled.

[0017] Furthermore, by combining the Swiss cheese model with FMEA analysis, the risk management of power generation systems can become more systematic and scientific. By defining clear defense modules, building decision trees or logic flow charts, and dynamically selecting and configuring defense modules, the efficiency and effectiveness of risk prevention and control can be significantly improved. At the same time, this approach also helps to promote risk awareness and collaboration within the organization, providing strong guarantees for the stable operation of the power generation system.

[0018] Furthermore, by integrating the Swiss cheese model with FMEA, and combining the detailed analysis of FMEA with the defense layer perspective of the Swiss cheese model, risk mitigation measures can be formulated, which can systematically mitigate the risks brought by high RPN value failure modes in the power generation system and improve the overall safety and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings in the specification are used to provide further understanding of the present invention and constitute a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0020] Figure 1 The present invention is a flow chart of a comprehensive risk management method for power generation equipment based on the FMEA-Swiss cheese model.

[0021] Figure 2 This is a process diagram of a comprehensive risk management method for power generation equipment based on the FMEA-Swiss cheese model of the present invention. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0023] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0024] Embodiment 1 See also Figure 1 ,A comprehensive risk management method for power generation equipment based on FMEA-Swiss cheese model includes the following steps: S1, defining the key components and process steps of the power generation system; S2. Analyze each key component and process step using FMEA. The specific analysis using FMEA is as follows: Conduct failure mode and effect analysis on power generation equipment. After identifying the potential failure mode of power generation equipment, determine the failure cause of the potential failure mode and evaluate the failure consequence of the potential failure mode, and calculate the RPN of the potential failure mode. S3. Define defense modules using the Swiss cheese model and analyze how each potential failure mode identified by FMEA passes through each defense layer; S4. Based on the analysis results of FMEA, a decision tree or logic flow chart is constructed to provide a decision path for each potential failure mode. The decision path guides the selection of defense module combinations for potential failure modes based on the RPN value of the potential failure mode. Combining the analysis of FMEA in S2 and the defense layer perspective of the Swiss cheese model in S3, risk mitigation measures are formulated. S5. Develop a risk management plan using the risk mitigation measures in S4 and review the FMEA and Swiss cheese model regularly.

[0025] This embodiment provides a comprehensive risk management method for power generation equipment based on the FMEA-Swiss cheese model. The specific process is as follows: Figure 2As shown: Step 1: System and process definition Identify the key components and operating processes of the power generation system.

[0026] Step 2: FMEA Implementation Perform FMEA on each critical component and process to identify potential failure modes, causes and effects.

[0027] 1. Identify potential failure modes: For each component or step, identify all potential ways that the system may fail to function.

[0028] 2. Determine the cause of the failure: For each failure mode, identify all possible causes that may have caused the failure to occur.

[0029] 3. Evaluate the consequences of failure: Analyze the impact of failure modes on system functions, safety, reliability, etc. if they occur.

[0030] 4. Calculation of RPN (Risk Priority Number) In the FMEA process, each potential failure mode is evaluated by three parameters: severity (S), probability of occurrence (O), and difficulty of detection (D). RPN is the product of these three parameters, that is, RPN = S × O × D, which is used to measure the relative priority of risks.

[0031] The high-risk failure modes identified by the RPN value are directly associated with specific defense layers, determining the defense layers that these failure modes can penetrate and the defense measures that need to be strengthened.

[0032] As the operating environment changes and new risks emerge, RPN values ​​can be recalculated to reflect these changes, and the defense layer analysis can be updated to ensure risk management measures remain current and effective.

[0033] The main steps of FMEA include: clarifying the object and scope of FMEA analysis, including which parts of the product or process need to be analyzed by FMEA. Forming a cross-functional team, including experts in design, manufacturing, quality, reliability, service and other fields, to ensure the comprehensiveness and accuracy of FMEA analysis. Clarifying the functional requirements that the product or process needs to meet, these requirements will serve as the basis for subsequent analysis. Analyzing the possible failure modes of the product or process, that is, the ways in which the product or process does not meet the functional requirements. For each failure mode, analyze and determine its possible causes. Evaluate the impact of each failure mode on product or system performance, safety, reliability and customer satisfaction. The risk priority number (RPN) is usually used to quantify the risk level of each failure mode. RPN is the product of the severity (S), frequency (O) and difficulty of detection (D) of the failure mode. For high-risk failure modes, formulate and implement preventive measures to reduce their frequency, mitigate their impact or improve detection capabilities. Record the results of the FMEA analysis in a document and update the FMEA analysis in a timely manner when changes occur in the product or process.

[0034] Advantages of FMEA: FMEA can identify potential failure modes before a product or process actually fails, so that measures can be taken in advance to prevent failures; FMEA provides a structured approach to analyzing products or processes to ensure that all relevant aspects are taken into account; FMEA analysis requires the participation of cross-functional teams, which helps promote communication and collaboration between different departments; FMEA is a dynamic process, and as products or processes change and experience accumulates, FMEA analysis needs to be continuously updated and improved.

[0035] In the design and operation of power generation systems, FMEA can help identify potential failure modes, assess their impact on system stability and reliability, and develop effective preventive measures, thereby improving the overall performance and safety of the power generation system.

[0036] Step 3: Swiss cheese model application Think of each component of the power generation system as layers of defense: design safety, operating procedures, maintenance plans, emergency measures, etc.

[0037] For each failure mode identified through FMEA, analyze how it could traverse these layers of defense.

[0038] 1. Phase 1: Preparation (1) Define defense modules: First, a series of defense modules need to be defined, each targeting a specific type of failure mode or risk level. These modules can be divided into three categories: basic defense, enhanced defense, and emergency response.

[0039] Basic Defense: These are the most basic preventive measures designed to reduce the likelihood of a failure or mitigate its consequences. For example, using high-quality materials and components, implementing basic safety standards and operating procedures, and performing regular preventive maintenance.

[0040] Enhanced defenses: When basic defenses are not sufficient to fully control the risk, additional defenses are needed. This may include more complex monitoring systems, redundant systems, automated controls, and more rigorous training procedures.

[0041] Emergency response: When a failure occurs, a quick and effective response is required to mitigate its impact. This includes emergency plans, emergency shutdown procedures, troubleshooting and repair processes, and the preparation of necessary resources (such as spare parts and professional teams).

[0042] (2) Failure mode analysis: Determine the RPN value of each failure mode through FMEA analysis, and determine the potential failure modes of each component or process in the power generation system through FMEA (failure mode and effects analysis). Score each failure mode and calculate the RPN (risk priority number), which is usually based on three factors: the product of occurrence (O), severity (S) and detection (D). Sort the failure modes according to the RPN value, giving priority to high-risk items.

[0043] 2. Phase 2: Build a decision tree or logic flow chart Based on the results of FMEA, a decision tree or logic flow chart is constructed to provide a decision path for each failure mode. This path guides the selection of the appropriate combination of defense modules based on the RPN value of the failure mode.

[0044] Construct a decision tree: Take the RPN value of the fault mode as input and construct a decision tree. Each branch represents a different RPN value range and points to the corresponding defense measure selection.

[0045] Logical flow chart: More intuitively displays the logical process from fault mode identification to defense measure selection. The flow chart can include conditional judgment (such as whether the RPN value exceeds a certain threshold), decision point (which defense module to choose) and final action (implementation of defense measures).

[0046] In the flowchart, clearly mark the criteria (such as RPN value threshold) and recommended defense module combination for each decision point.

[0047] The logic flow chart shows which defense modules should be used if the RPN value of a failure mode reaches a certain threshold. For example, for a failure mode with a high RPN value, the flow chart will recommend the use of a basic defense module in combination with one or more enhanced defense modules.

[0048] When constructing a decision tree or logic flow chart, in addition to providing a decision path based on the RPN value of each fault mode, it is also necessary to consider the coexistence of multiple high-priority fault modes. ① Based on the RPN value and the severity (S) of the potential fault, give priority to the fault mode that has the greatest impact on system safety and reliability. When the RPN values ​​of multiple fault modes are similar or equal, the fault mode with high severity is prioritized for processing based on the S value; ② For the coexistence of multiple fault modes in a complex system, multiple defense modules are allowed to be implemented in parallel. By allocating resources, more energy is invested in high-priority fault defense, while reserving some resources for the processing of the second-highest priority fault mode; ③ Establish a real-time monitoring mechanism for fault modes, dynamically adjust the decision path, and ensure that when a high RPN value fault mode is processed, the secondary priority fault can automatically enter the defense process.

[0049] 3. Phase 3: Module selection and combination The appropriate defense module is dynamically selected based on the currently analyzed failure mode and its RPN value. This approach enables the defense strategy to flexibly adapt to different risk situations. This requires the risk management team to be able to quickly assess the risk situation and make corresponding decisions.

[0050] After determining the required defense modules, further configure these modules to suit the specific situation. This includes adjusting system parameters, optimizing operating procedures, strengthening training, or updating maintenance plans. It is crucial to maintain the flexibility of the defense strategy. With the upgrade of technology, changes in operating conditions, or the emergence of new risks, the selection and configuration of defense modules need to be reviewed and adjusted regularly.

[0051] Step 4: Integrate FMEA and Swiss Cheese Model Combining the detailed analysis of FMEA and the defense layer perspective of the Swiss cheese model, develop risk mitigation measures: 1. Phase 1: For each failure mode with a high RPN value, identify the corresponding defense layer defect (hole).

[0052] For each high RPN value failure mode identified through FMEA analysis, we will delve into the specific reasons why it can penetrate the various defense layers of the power generation system (such as design safety, operating procedures, maintenance plans, emergency measures, etc.), that is, identify the "holes" or defects in these defense layers.

[0053] First, review the results of the FMEA analysis in detail, especially the failure modes with high RPN values ​​and their causes and effects. Map each failure mode to the various defense layers of the power generation system and analyze how the failure propagates between these layers. In each defense layer, identify the specific defects or deficiencies that allow the failure to penetrate. These are the "holes" that need to be filled.

[0054] 2. Phase 2: Design targeted improvement measures to "fill" these holes, such as improving design, strengthening operation training, and adding detection methods. For the holes in the defense layer identified in Phase 1, design and implement specific improvement measures to "fill" these holes to enhance the overall defense capabilities of the system.

[0055] For each hole, develop a detailed improvement plan, including the content, methods, responsible persons, and timetable of the improvement. If the hole is related to the design, consider improving the design standards, using more reliable materials or components, adding redundant systems, etc. If the hole is related to the behavior or lack of knowledge of the operator, strengthen operation training, improve the safety awareness and skill level of employees. If the hole is related to insufficient detection capabilities, introduce more advanced detection technology and equipment to improve the early detection rate of faults. If the hole is related to insufficient maintenance, optimize the maintenance plan, increase the maintenance frequency, or improve the maintenance method.

[0056] 3. Phase 3: Implement cross-layer prevention measures to ensure that even if one defense layer fails, other layers can prevent the development of the failure.

[0057] On the basis of filling the holes in a single defense layer, cross-layer preventive measures are further implemented to ensure that even if one defense layer fails, other layers can effectively prevent the development of the fault, thereby preventing the collapse of the entire system.

[0058] Ensure that the power generation system has a multi-layer defense mechanism, and each layer can independently identify and respond to potential failures. Promote information sharing and collaboration between defense layers to ensure that when a problem is found in one layer, the defense measures of other layers can be quickly notified and activated. Regularly review and exercise the multi-layer defense system to evaluate its effectiveness and identify potential problems in a timely manner. Based on feedback and lessons learned from actual operation, continuously optimize the multi-layer defense system to improve its adaptability and flexibility.

[0059] Step 5: Risk Management Planning and Monitoring Develop an ongoing risk management program and review FMEA and Swiss cheese model analysis regularly, especially when major changes occur (such as technology upgrades, changes in operating conditions, etc.).

[0060] Set a fixed review cycle (such as quarterly, half-yearly or annually) to review the risk management plan. The review content includes risk identification, risk assessment, effectiveness of response strategies, etc. In each review, update the FMEA analysis to reflect the latest technology upgrades, changes in operating conditions, etc. Review the implementation of preventive measures and detection measures and evaluate their effectiveness. Use the Swiss cheese model to analyze the vulnerabilities and changes in each layer of the defense system. According to the analysis results, adjust and improve the defense measures to ensure the effectiveness of each layer of the defense system. Conduct special risk assessments before major changes such as technology upgrades and changes in operating conditions. Identify new risks brought about by the changes and evaluate their impact on the existing risk management plan. Adjust the risk management plan based on the results of the change risk assessment. Update the FMEA analysis and Swiss cheese model analysis to ensure that they reflect the latest risk status. Implement the adjusted risk management plan and monitor the implementation process. Timely discover and solve problems that arise during the implementation process to ensure the effective implementation of the risk management plan.

[0061] Embodiment 2 An integrated risk management system for power generation equipment based on the FMEA-Swiss cheese model, including an FMEA analysis module for defining the scope and functions of the integrated risk management system for power generation equipment, identifying potential failure modes, identifying failure causes and failure consequences, calculating RPN values, and formulating mitigation measures; Swiss cheese analysis module, used to identify defense layers, assess defense layer deficiencies, analyze interactions between deficiencies, and develop defense measures; The failure mode and defense layer module is integrated to obtain the defense strategy decision logic after integrating the mitigation measures of the FMEA analysis module and the defense measures of the Swiss cheese analysis module. The defense strategy decision logic is modularized to obtain a modular defense strategy decision logic. According to the modular defense strategy decision logic, the optimized defense measures based on RPN are obtained. The modular defense strategy decision logic includes a low-risk basic module, a medium-risk basic enhancement module, and a high-risk basic enhancement emergency module.

[0062] The FMEA analysis module calculates the RPN value and maps it to the defense layer identified by the Swiss cheese analysis module; the logical decision process input of the FMEA analysis module and the Swiss cheese analysis module integrates the defense strategy decision logic of the failure mode and defense layer module for modularization; the RPN-based optimized defense measures of the failure mode and defense layer module are dynamically fed back to the potential failure mode identified by the FMEA analysis module; the RPN-based optimized defense measures of the failure mode and defense layer module are dynamically adjusted to the defense layer identified by the Swiss cheese analysis module.

[0063] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit its protection scope. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that after reading the present invention, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the invention, but these changes, modifications or equivalent substitutions are all within the protection scope of the pending claims of the invention.

Claims

1. A comprehensive risk management method for power generation equipment based on FMEA-Swiss cheese model, characterized in that: The following steps are involved: S1. Define the key components and process steps of the power generation system; S2. Analyze each key component and process step using FMEA. The specific analysis using FMEA is as follows: Conduct failure mode and effect analysis on power generation equipment. After identifying the potential failure mode of power generation equipment, determine the failure cause of the potential failure mode and evaluate the failure consequence of the potential failure mode, and calculate the RPN of the potential failure mode. S3. Define defense modules using the Swiss cheese model and analyze how each potential failure mode identified by FMEA passes through each defense layer; S4. Based on the analysis results of FMEA, a decision tree or logic flow chart is constructed to provide a decision path for each potential failure mode. The decision path guides the selection of defense module combinations for potential failure modes based on the RPN value of the potential failure mode. Combining the analysis of FMEA in S2 and the defense layer perspective of the Swiss cheese model in S3, risk mitigation measures are formulated. S5. Develop a risk management plan using the risk mitigation measures in S4 and review the FMEA and Swiss cheese model regularly.

2. A comprehensive risk management method for power generation equipment based on FMEA-Swiss cheese model according to claim 1, characterized in that: Identification of potential failure modes of power generation equipment in S2 includes potential ways to cause system functional failure; Failure causes include all causes that lead to any potential failure mode; Failure consequences include the impact of any potential failure mode on system function, safety and reliability; The calculation formula used to calculate the RPN for a potential failure mode is as follows: RPN = S × O × D Among them, RPN is the risk priority number. In the FMEA process, the evaluation parameters of each potential failure mode include S, O and D, S is the severity, O is the probability of occurrence, and D is the difficulty of detection.

3. The comprehensive risk management method for power generation equipment based on FMEA-Swiss cheese model according to claim 1 is characterized in that: S3 includes defining defense modules and potential failure mode analysis, building decision trees or logic flow charts, and selecting and combining modules.

4. A comprehensive risk management method for power generation equipment based on FMEA-Swiss cheese model according to claim 3, characterized in that: Defining defense modules and failure mode analysis is as follows: defining defense modules, each of which corresponds to different types of potential failure modes or risk levels; the types of defense modules include basic defense, enhanced defense, and emergency response.

5. A comprehensive risk management method for power generation equipment based on FMEA-Swiss cheese model according to claim 4, characterized in that: S4 is specifically as follows: based on the RPN value of each potential failure mode determined by FMEA, a decision tree or logic flow chart is constructed. The decision tree or logic flow chart provides a decision path for each potential failure mode. The potential failure mode selects a defense module for combination through the decision path using the RPN value of the failure mode; the logic flow chart shows the defense module used when the RPN value of the potential failure mode reaches the threshold.

6. A comprehensive risk management method for power generation equipment based on FMEA-Swiss cheese model according to claim 5, characterized in that: The defense modules are selected for combination using the RPN value of the failure mode as follows: the defense modules are dynamically selected for configuration according to the current potential failure mode and its RPN value.

7. The comprehensive risk management method for power generation equipment based on FMEA-Swiss cheese model according to claim 1 is characterized in that: S4 is specifically: Identify the defense layer defects of potential failure modes, and build cross-level prevention measures and improvement measures to repair the defense layer defects.

8. The comprehensive risk management method for power generation equipment based on FMEA-Swiss cheese model according to claim 1 is characterized in that: The risk management plan is a risk management plan for when the power generation system technology is upgraded or the operating conditions of the power generation equipment change.

9. A comprehensive risk management system for power generation equipment based on FMEA-Swiss cheese model, characterized in that: Includes FMEA analysis module, which is used to define the scope and function of the integrated risk management system for power generation equipment, identify potential failure modes, identify the causes and consequences of failures, calculate RPN values, and develop mitigation measures; Swiss cheese analysis module, used to identify defense layers, assess defense layer deficiencies, analyze interactions between deficiencies, and develop defense measures; The failure mode and defense layer module is integrated to obtain the defense strategy decision logic after integrating the mitigation measures of the FMEA analysis module and the defense measures of the Swiss cheese analysis module. The defense strategy decision logic is modularized to obtain a modular defense strategy decision logic. According to the modular defense strategy decision logic, the optimized defense measures based on RPN are obtained. The modular defense strategy decision logic includes a low-risk basic module, a medium-risk basic enhancement module, and a high-risk basic enhancement emergency module.

10. The integrated risk management system for power generation equipment based on FMEA-Swiss cheese model according to claim 9, characterized in that: The FMEA analysis module calculates the RPN value and maps it to the defense layer identified by the Swiss cheese analysis module; The logical decision process input of the FMEA analysis module and the Swiss cheese analysis module integrates the defense strategy decision logic of the failure mode and defense layer module to modularize; Integrate the RPN-based optimized defense measures of the failure mode and defense layer module to dynamically feed back the potential failure modes identified by the FMEA analysis module; The RPN-based optimized defense measures that integrate the failure mode and defense layer modules dynamically adjust the defense layers identified by the Swiss cheese analysis module.

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