Power station boiler digital integrity management system and management efficiency evaluation method

Abstract

The invention belongs to the field of power station boiler accident risk prevention and control management, and particularly relates to a power station boiler digital integrity management system and a management efficiency evaluation method. The system comprises an enterprise data center module, a boiler data center module, a pressure-bearing component risk evaluation module, a pressure-bearing component integrity evaluation module, a maintenance and decision module, an emergency management module, a safety knowledge base module, an efficiency evaluation module and a large screen display module, and the modules realize data dynamic closed-loop interaction through data ports. According to the management efficiency evaluation method, a power station boiler integrity management efficiency evaluation index system is constructed from two aspects of an integrity management process and a management effect, and a management process score is obtained by adopting a queuing theory method; obtaining a management effect score by using a data envelope analysis method; and on the basis, a result compensation coefficient is introduced to calculate a final comprehensive management efficiency score, so that the comprehensive, objective and reasonable evaluation effect is ensured.

Description

Technical Field

[0001] This invention belongs to the field of power plant boiler accident risk prevention and control management, and particularly relates to a digital integrity management system for power plant boilers and a method for evaluating management effectiveness. Background Technology

[0002] Power plant boilers are an indispensable part of the main thermal equipment in the power generation process. As an important energy conversion device, they occupy a vital position in national economic production and daily life. With the rapid development of my country's economy and the continuous growth of energy demand, the development prospects of power plant boilers are very broad. In recent years, in order to achieve the dual carbon goals of "carbon neutrality and carbon peaking," my country's energy transition strategy has been continuously deepened, and new power platform systems have been rapidly constructed. Power plant boilers are constantly developing towards high efficiency, environmental protection, safety, diversification, and intelligence. However, due to the characteristics of high operating temperature, high pressure, and long cycle of power plant boilers, there are many potential risks such as boiler explosion, fire, and burns. Their safe and stable operation has always been a major concern in the industry. With the increase in power generation demand and the improvement of energy conservation and environmental protection requirements, the requirements for parameters such as pressure rating, outlet temperature, and pipe type of power plant boilers are constantly increasing. New power plant boilers and clean combustion technologies are constantly being introduced. The continuous application of new equipment, new technologies, and new materials brings new safety risks. Therefore, in addition to the need to improve the boiler body control system, more advanced power plant boiler management methods are also needed in the daily operation and maintenance process to improve the safety of power plant boiler operation and protect the lives of employees and the safety of equipment and property.

[0003] Currently, my country lacks a specialized safety management system for power plant boilers. Safety management is often simply and crudely categorized under the enterprise's safety management system. This frequently leads to incomplete management elements, insufficient management methods, and poor management effectiveness, resulting in a lack of risk control and a precarious situation of frequent power plant boiler accidents. Integrity management, a newly emerging safety management method in recent years, combines platform-based systematic technological improvements with a standardized management system to identify, evaluate, and detect factors that may affect the safety status of equipment during operation, and formulate corresponding risk control strategies to maximize the integrity of critical equipment throughout its life cycle. This method has already achieved widespread application and good results in pressure pipelines in the petrochemical, urban gas, and other fields.

[0004] Power plant boilers consist of pressure-bearing components such as water-cooled walls, economizers, superheaters, reheaters, boiler drums, steam-water separators, headers, desuperheaters, and steam-water pipelines. In other words, they are primarily composed of pressure-bearing equipment and pipelines. Therefore, integrity management theory has a high degree of applicability and value in power plant boiler management. However, unlike pressure-bearing pipelines, power plant boilers have a greater variety of pressure-bearing components with diverse structures, making management more complex. This necessitates the integration of digital, information-based, and intelligent management methods. Furthermore, to ensure effective operation, a comprehensive evaluation of the integrity management system's operational efficiency is required. This evaluation aims to identify shortcomings through quantitative performance scores, enabling dynamic, cyclical, and continuous improvement, thereby effectively enhancing the modern safety management system and governance capabilities of power plant boilers. This will provide new control methods and working tools for the modern safety management of power plant boilers. Summary of the Invention

[0005] The purpose of this invention is to provide a digital integrity management system for power plant boilers and a method for evaluating management effectiveness, in order to address the current problems of incomplete management elements, insufficient management methods, and poor management results in power plant boilers.

[0006] The present invention discloses a digital integrity management system for power plant boilers, comprising nine parts: an enterprise data center module, a boiler data center module, a pressure-bearing component risk assessment module, a pressure-bearing component integrity assessment module, a maintenance and decision-making module, an emergency management module, a safety knowledge information database module, an efficiency evaluation module, and a large-screen display module. Each module achieves dynamic closed-loop data interaction through data ports.

[0007] The enterprise data center module is used to store and collect enterprise information, including basic enterprise information, organizational structure, and personnel management. Basic enterprise information includes the location of the power plant boiler company, its work area share, company type, establishment date, registered capital, and business scope. The organizational structure is displayed in the form of a chart. Personnel management includes the names, departments, positions, contact numbers, qualification certificates, and educational backgrounds of all employees.

[0008] The boiler data center module stores and collects historical information for all power plant boilers within the company, including basic data, downtime statistics, and accident statistics. Basic data displays fundamental information about all boilers, including equipment code, model, and operating status. Downtime statistics primarily include the number of unplanned and planned downtimes this month, their causes, and start and end times. Cumulative accident statistics mainly include the types of accidents, property damage, personal injury, and causes that have occurred since commissioning.

[0009] The pressure-bearing component risk assessment module is used to assess the risks of pressure-bearing components in power plant boilers, obtaining risk values ​​and risk levels. Based on preliminary statistical data, the main pressure-bearing components of the power plant boiler are assessed for risk, and the risk levels are divided into four different levels: extremely low risk, low risk, medium risk, and high risk, and are assigned four colors: blue, yellow, orange, and red, respectively, according to the different levels.

[0010] The pressure-bearing component integrity assessment module is used to evaluate the integrity status of pressure-bearing components. Based on inspection methods and results, it assesses the damage status, safety status, remaining strength, and remaining life of medium- and high-risk components, thereby clarifying the current health status and future operational capability of the components. This includes current status identification and future status prediction. Current status identification includes inspection date, inspection object, inspection method, and inspection results. Future status prediction includes the prediction object, prediction method, and prediction results.

[0011] The Maintenance and Decision-Making module is used to formulate maintenance strategies for components. This involves developing and optimizing maintenance plans for pressure-bearing components with excessive damage, abnormal safety conditions, or insufficient remaining strength and lifespan. This includes daily inspections and maintenance management. Daily inspections include statistics on the number of inspections, specific parts of the boiler inspected, inspection time, inspection personnel, and problems encountered. Maintenance management includes work order allocation, work order processing, work order review, final feedback on work orders, and the personnel involved in each step, as well as the time and cost.

[0012] The emergency management module stores and collects emergency management-related documents for the enterprise, including four sub-modules: emergency plans, emergency rescue teams, emergency supplies, and emergency response measures. The emergency plans sub-module includes the plan type, document, preparation time, and preparation team. The emergency rescue teams sub-module stores information on the number of personnel in the emergency team, including names, qualifications, responsibilities, and contact information. The emergency supplies sub-module records the types and quantities of emergency supplies currently available to the enterprise. Emergency response measures include the name, definition, phenomenon, cause, and response measures for the emergency situation.

[0013] The safety knowledge information database module is used to store and collect relevant laws, regulations, industry standards, local standards, etc., and specifically includes functions such as standard code, name, online reading, and download.

[0014] The performance evaluation module is used to evaluate the overall management effectiveness of power plant boiler enterprises. It employs management performance evaluation methods to quantify the enterprise's overall management from two perspectives: the completeness of the management process and the boiler's own condition. This results in a true reflection of the power plant boiler enterprise's complete management and any shortcomings, providing support for decision-making regarding the enterprise's management level.

[0015] The large-screen display module facilitates subsequent monitoring by the enterprise. It intuitively displays important boiler data, such as the boiler's risk level, number of inspections, and inspection dates.

[0016] The power plant boiler digital integrity management performance evaluation method described in this invention is a comprehensive evaluation of the management process and effectiveness of power plant boiler integrity management. It is mainly used to obtain an actual management score and to address and improve shortcomings for continuous enhancement. The method specifically includes the following steps:

[0017] The management effectiveness evaluation method for a digital integrity management system for power plant boilers includes the following steps:

[0018] S1. Establish an efficiency evaluation index system for the digital integrity management of power plant boilers from two dimensions: management process and management effect.

[0019] S2, use queuing theory to determine the weights of each indicator in the management process and calculate the management process score;

[0020] S3. Use data envelopment analysis to obtain management effectiveness values ​​and calculate management performance scores.

[0021] S4, determine the consequence compensation coefficient based on the severity of accidents that occur to the company during the assessment period;

[0022] S5 calculates the final comprehensive management effectiveness score using management process score, management effect score, and consequence compensation coefficient, and classifies the level based on the final comprehensive management effectiveness score.

[0023] The performance evaluation index system of the power plant boiler management system described in S1 includes integrity management process indicators and integrity management effect indicators. The integrity management process indicators include data collection indicators, risk assessment indicators, integrity evaluation indicators, maintenance and decision-making indicators, and emergency management indicators. Data collection indicators include the completeness of enterprise information, the accuracy of boiler data, and the integrity of boiler data. Risk assessment indicators are divided into the selection of evaluation methods, the coverage of risk assessment, and the acceptability of evaluation results. Integrity evaluation indicators include the selection of inspection methods, applicability evaluation, and third-party inspection. Maintenance and decision-making indicators include personnel inspection management, inspection equipment status, and equipment maintenance status. Emergency management indicators include the development of emergency plans, the status of emergency supplies and equipment, the professionalism of emergency rescue teams, and emergency drills and accident handling. The integrity management effect indicators include input indicators and output indicators. Input indicators include per capita inspection cost, per capita maintenance cost, and number of emergency rescue team members. Output indicators include work efficiency, normal operating rate, and steam production completion rate.

[0024] Furthermore, the definitions of work efficiency, normal uptime rate, and completion rate are as follows:

[0025] Work efficiency = Actual steam output of power plant boiler ÷ Actual operating time of power plant boiler;

[0026] Normal operating rate = 1 ÷ planned shutdown time;

[0027] Steam production completion rate = Actual steam output of power plant boiler ÷ Expected steam output of power plant boiler.

[0028] S2 includes the following steps:

[0029] S2-1: Rank the importance of the integrity management process indicators;

[0030] S2-2: Using queuing theory, calculate the weights of each integrity management process indicator. The calculation method is as follows:

[0031]

[0032] In the formula, ω i Let i be the weight of each integrity management process indicator, i be the ranking value, and n be the number of integrity management process indicators.

[0033] S2-3: ω i After normalization, we get

[0034] S2-4: Calculate the scoring criteria for each integrity management process indicator. The calculation formula is as follows:

[0035]

[0036] S2-5: n experts will score each item according to the company's actual situation and the scoring criteria, and the average score will be used as the actual score for the corresponding integrity management process indicator. The management process score will be calculated using the following formula:

[0037]

[0038] Where D1 is the management process score, n is the number of integrity management process indicators, and x i Let x′ be the scoring criterion for the i-th integrity management process indicator. i This represents the actual score of the i-th integrity management process indicator.

[0039] S3 includes the following steps:

[0040] S3-1: Based on the integrity management effectiveness index values, establish an input matrix X and an output matrix Y, where there are n enterprises that need to be evaluated, and each enterprise has m input indicators and s output indicators.

[0041] S3-2: Using the DEA method, evaluate the j-th firm and solve for its efficiency value θ.

[0042]

[0043] For ease of calculation, it is transformed into an equivalent linear programming model:

[0044]

[0045] Where, x j =(x 1j ,x 2j ,…,x mj ) represents the input indicator value of the j-th enterprise; y j =(y 1j ,y 2j ,…,y sj ) represents the output indicator value of the j-th firm; u represents the weight of the input indicator; v represents the weight of the output indicator; λ j S is a parameter. + S - Let θ be a slack variable, and let θ represent the relative effectiveness of firm j, i.e., the efficiency value of firm j.

[0046] S3-3: Calculate the management effectiveness score. The calculation formula is as follows:

[0047] D2=θ×100

[0048] Where D2 is the management effectiveness score and θ is the enterprise's efficiency value.

[0049] In S4, the consequence compensation coefficient is:

[0050] Accident level Accident meaning Consequence compensation coefficient Level 0 accident No accident occurred. 1 Level 1 accident No personal injury or minor injury, or property damage less than 100,000 yuan. 0.95 Level 2 accident Serious personal injury, or property damage exceeding 100,000 yuan but less than 500,000 yuan. 0.85 Level 3 accident One or two deaths, or property damage exceeding 500,000 yuan but less than 1,500,000 yuan. 0.60 Level 4 accident 3 to 9 deaths, or property damage exceeding 1.5 million yuan but less than 10 million yuan. 0.40 Level 5 accident Ten or more deaths, or property damage exceeding 10 million yuan. 0

[0051] In S5, the final comprehensive management effectiveness score is calculated using the following formula:

[0052]

[0053] Where D is the overall management effectiveness score, D1 is the management process score, D2 is the management effect score, and C is the consequence compensation coefficient.

[0054] Furthermore, based on the final comprehensive management effectiveness score, the enterprise's comprehensive management effectiveness level is determined. The enterprise's comprehensive management effectiveness level is divided into four levels: A, B, C, and D.

[0055]

[0056]

[0057] This invention proposes a digital integrity management system for power plant boilers and a method for evaluating management effectiveness, addressing the current problems of incomplete management elements, insufficient management methods, and poor management results in power plant boilers. This invention constructs an evaluation index system for the integrity management effectiveness of power plant boilers from two aspects: the integrity management process and management effect, providing dual assurance for evaluating the effectiveness of power plant boiler integrity management and identifying weaknesses in the management process.

[0058] This invention proposes a power plant boiler efficiency evaluation method based on queuing theory and DEA. Based on queuing theory, weights are calculated for integrity process indicators to determine the scoring criteria for each indicator in the management process. A subjective score for the enterprise's integrity management operation is obtained based on the enterprise's actual situation. Combined with objective data, the input-output ratio of the enterprise is calculated using DEA to obtain an objective score for the enterprise's integrity management, effectively avoiding the limitations of subjective scoring. The evaluation results are further validated using the number of casualties and property damage from accidents, employing a consequence compensation coefficient to make the evaluation results more reasonable.

[0059] The performance evaluation method proposed in this invention can comprehensively reflect the actual management level of power plant boiler enterprises, which is conducive to enterprises analyzing the deficiencies in management, discovering the shortcomings in the integrity management process, clarifying the direction of improvement, thereby promoting all levels of units and personnel to carry out various activities in accordance with the requirements of integrity management, continuously improving the effectiveness and timeliness of equipment and facility integrity management, and ultimately achieving the best balance between equipment and facility performance, maintenance costs, and operational risks.

[0060] This invention enables visualization of the entire process of power plant boiler integrity management, creating integrity files for each stage, dynamically monitoring and promptly grasping the risk status of power plant boilers.

[0061] This invention applies integrity management theory to the research of relevant technical modules for power plant boilers, including data acquisition, risk assessment, integrity assessment, maintenance and decision-making, emergency management, and performance evaluation, providing a scientific management platform for power plant boiler management. Attached Figure Description

[0062] Figure 1 This invention relates to the digital integrity management system for power plant boilers.

[0063] Figure 2 This is a flowchart of the performance evaluation method described in this invention. Detailed Implementation

[0064] Example 1

[0065] Reference Figure 1A digital integrity management system for power plant boilers includes nine modules: an enterprise data center module, a boiler data center module, a pressure-bearing component risk assessment module, a pressure-bearing component integrity assessment module, a maintenance and decision-making module, an efficiency evaluation module, an emergency management module, a safety knowledge information database module, and a large-screen display module. Each module achieves dynamic closed-loop data interaction through data ports.

[0066] Reference Figure 1 The company organizes and categorizes its own information and boiler data, synchronizing them promptly to the company's data center module and the boiler's data center module. Based on data statistics, semi-quantitative risk assessment results are synchronized to the pressure-bearing component risk assessment module. Inspection results and predictions for medium- and high-risk components are recorded in the pressure-bearing component integrity assessment module. Based on laws, regulations, and handling procedures in the safety knowledge information database module, the company records medium- and high-risk maintenance work arrangements in the maintenance and decision-making module. Relevant emergency management information is recorded in the emergency management module. The company's comprehensive management score is recorded in the performance evaluation module. All of this information is interconnected with the company's large-screen display module, which visually displays key boiler data, such as risk level, inspection frequency, and inspection dates, facilitating subsequent monitoring.

[0067] The enterprise data center module includes basic enterprise information, organizational structure, and personnel management. Basic enterprise information includes the location of the power plant boiler enterprise, the proportion of each work area, enterprise nature, establishment time, registered capital, and business scope. The organizational structure is displayed in the form of a structure diagram. Personnel management includes employee names, departments, positions, contact numbers, qualification certificates, and education. Operators can add, delete, and modify personnel in the personnel management section.

[0068] The boiler data center module includes basic information, downtime statistics, and accident statistics. Basic information displays fundamental details about all boilers in the company, including equipment code, model, and usage status. Operators can access specific information about a particular boiler by clicking "Details." This specific information includes the boiler's floor plan, 3D model, specifications, performance parameters, maintenance records, and risk assessment data. Downtime statistics primarily include the number of unplanned and planned downtimes since the beginning of the month, their causes, and start and end times. Cumulative accident statistics mainly include the types of accidents, property damage, personal injury, and causes of accidents since commissioning.

[0069] The pressure-bearing component risk assessment module is the foundation of the integrity assessment and maintenance and decision-making modules. Due to the complexity and diversity of pressure-bearing equipment in power plant boilers, in order to save maintenance and inspection resources and ensure the safety of power plant boilers to a greater extent, it is necessary to prioritize the allocation of inspection resources according to the risk level of the pressure-bearing equipment.

[0070] The risk assessment module for pressure-bearing components uses a semi-quantitative assessment method (referencing GB 30581-2014). By accessing partial data from the enterprise data center module and the boiler data center module, it calculates the risk level of the pressure-bearing components in the power plant boiler. Simultaneously, it assigns four colors—red, orange, yellow, and blue—to the extremely low, low, medium, and high risk levels of the pressure-bearing components, respectively. The results are displayed in real-time on the 3D model of the power plant boiler, providing corresponding statistical charts and highlighting newly added red and orange risk areas, along with a risk analysis report.

[0071] The pressure-bearing component integrity assessment module assesses the integrity status of medium- and high-risk pressure-bearing components based on risk assessment, that is, it clarifies the current health status of pressure-bearing equipment and its future ability to operate healthily; the pressure-bearing component integrity assessment module includes current status identification and future status prediction.

[0072] The current status identification is used to collect and record the inspection results of the boiler by third-party inspection agencies over the years, including the inspection date, the name of the inspector, the inspection qualification, the inspection method, and the inspection result. The inspection method includes macroscopic inspection, wall thickness measurement, surface defect detection, metallographic inspection, creep detection, and carburization detection. The inspection result includes whether there is bending, severe bending, mechanical damage, environmental damage, etc. on a macroscopic scale, the true wall thickness value of each measuring point, whether there are defects or cracks on the surface, and the creep detection result includes the measured value of the outer diameter of each measuring point.

[0073] The aforementioned future state identification and prediction is used to collect stress verification results of medium- and high-risk components; based on the inspection data such as the test pressure, measured outer diameter, and measured wall thickness of the pressure-bearing components of the power plant boiler, the remaining strength of the pressure-bearing components is verified by calculating the stress; when the stress of the pressure-bearing components of the power plant boiler is higher than the allowable stress of the material, the evaluation result should be unsatisfactory, and the components should be replaced immediately; when the stress of the pressure-bearing components of the power plant boiler is still within the allowable stress of the material, the evaluation result is satisfactory, and certain measures are taken to control the risk.

[0074] The maintenance and decision-making module makes maintenance work arrangements based on the integrity evaluation results of pressure equipment. Based on the integrity evaluation results, the company arranges daily inspections and maintenance. Daily inspections include statistics on the number of inspections, specific parts of the boiler inspected, inspection time, inspection personnel, and problems encountered. The platform system will generate maintenance work orders for pressure components and implement hierarchical approval, including work order allocation, work order processing, work order review, and final feedback. In addition, it records the person in charge of each step, as well as the time and cost.

[0075] The emergency management module stores and collects emergency management-related documents for the enterprise. It includes four sub-modules: emergency plans, emergency rescue teams, emergency supplies, and emergency response measures. The emergency plan sub-module includes the plan type, document, preparation time, and preparation team. The emergency rescue team sub-module stores information on the number of personnel in the emergency team, including names, qualifications, responsibilities, and contact information. The emergency supplies sub-module records the types and quantities of emergency supplies currently available to the enterprise. Emergency response measures include the name, definition, phenomenon, cause, and response measures for the emergency situation.

[0076] The safety knowledge information database module is used to store and collect relevant laws, regulations, industry standards, local standards, etc.; specifically, it includes functions such as standard code, name, online reading, and download.

[0077] The large-screen display module facilitates subsequent monitoring by the enterprise. It intuitively displays key boiler data, such as the boiler's risk level, number of inspections, and inspection dates.

[0078] Example 2

[0079] refer to Figure 2 The method for evaluating the effectiveness of digital integrity management of power plant boilers, using the digital integrity management system for power plant boilers described in Example 1, includes the following steps:

[0080] S1. Establish a power plant boiler management efficiency evaluation index system from two dimensions: management process and management effect.

[0081] The evaluation index system for the management effectiveness of power plant boilers includes indicators for the integrity management process and indicators for the integrity management effect.

[0082] S2, using queuing theory to determine the weights of each indicator in the implementation process and calculating the management process score, includes the following steps:

[0083] S2-1: Rank the importance of the integrity management process indicators;

[0084] S2-2: Using queuing theory, calculate the weights of each integrity management process indicator. The calculation method is as follows:

[0085]

[0086] In the formula, ω i Let i be the weight of each integrity management process indicator, i be the ranking value, and n be the number of integrity management process indicators.

[0087] S2-3: ω i After normalization, we get

[0088] S2-4: Calculate the scoring criteria for each integrity management process indicator. The calculation formula is as follows:

[0089]

[0090] S2-5: n experts will score each item according to the company's actual situation and the scoring criteria, and the average score will be used as the actual score for the corresponding integrity management process indicator. The management process score will be calculated using the following formula:

[0091]

[0092] Where D1 is the management process score, n is the number of integrity management process indicators, and x i Let x′ be the scoring criterion for the i-th integrity management process indicator. i This represents the actual score of the i-th integrity management process indicator.

[0093] S3, using data envelopment analysis to obtain the effectiveness value of enterprise management and calculate the management effectiveness score, includes the following steps:

[0094] S3-1: Based on the integrity management effectiveness index values, establish an input matrix X and an output matrix Y, where there are n enterprises that need to be evaluated, and each enterprise has m input indicators and s output indicators.

[0095] S3-2: Using the DEA method, evaluate the j-th firm and solve for its efficiency value θ.

[0096]

[0097] For ease of calculation, it is transformed into an equivalent linear programming model:

[0098]

[0099] Where, x j =(x 1j ,x 2j ,…,x mj ) represents the input indicator value of the j-th enterprise; y j =(y 1j ,y2j ,…,y sj ) represents the output indicator value of the j-th firm; u represents the weight of the input indicator; v represents the weight of the output indicator; λ j S is a parameter. + S - Let θ be a slack variable, and let θ represent the relative effectiveness of firm j, i.e., the efficiency value of firm j.

[0100] S3-3: Calculate the management effectiveness score. The calculation formula is as follows:

[0101] D2=θ×100

[0102] Where D2 is the management effectiveness score and θ is the enterprise's efficiency value.

[0103] S4. Determine the consequence compensation coefficient based on the severity of accidents that occurred to the company during the assessment period; the consequence compensation coefficient is:

[0104] Table 1 Consequence Compensation Coefficient

[0105] Accident level Accident meaning Consequence compensation coefficient Level 0 accident No accident occurred. 1 Level 1 accident No personal injury or minor injury, or property damage less than 100,000 yuan. 0.95 Level 2 accident Serious personal injury, or property damage exceeding 100,000 yuan but less than 500,000 yuan. 0.85 Level 3 accident One or two deaths, or property damage exceeding 500,000 yuan but less than 1,500,000 yuan. 0.60 Level 4 accident 3 to 9 deaths, or property damage exceeding 1.5 million yuan but less than 10 million yuan. 0.40 Level 5 accident Ten or more deaths, or property damage exceeding 10 million yuan. 0

[0106] S5 calculates the final comprehensive management effectiveness score using management process score, management effect score, and consequence compensation coefficient, and classifies the level based on the final comprehensive management effectiveness score.

[0107] The final comprehensive management effectiveness score is calculated using the following formula:

[0108]

[0109] Where D is the overall management effectiveness score, D1 is the management process score, D2 is the management effect score, and C is the consequence compensation coefficient.

[0110] Based on the performance score, the performance of power plant boiler integrity management is divided into four levels: A, B, C, and D, as detailed in Table 2.

[0111] Table 2 Management Effectiveness Evaluation Levels

[0112]

[0113] Specific applications

[0114] This study evaluates the effectiveness of the integrity management practices of two power plant boiler manufacturers, A and B, in a certain city in 2022. The basic equipment information is as follows: Company A's power plant boiler was put into operation in 2017, and its cumulative operating time as of 2022 was approximately 41,000 hours. Company B's power plant boiler was put into operation in 2015, and its cumulative operating time as of 2022 exceeded 48,843 hours. The basic evaluation data for the companies is shown in Table 3.

[0115] Table 3. Complete Basic Evaluation Data for Companies A and B in 2022

[0116]

[0117]

[0118] (1) Enterprises should establish an effectiveness evaluation index system for digital integrity management of power plant boilers based on their own actual situation, including integrity management process indicators and integrity management effect indicators. The integrity management process indicators include five primary indicators: data collection, risk assessment, integrity assessment, maintenance and decision-making, and emergency management; and 16 secondary indicators: completeness of enterprise information, accuracy of boiler data, integrity of boiler data, selection of evaluation methods, coverage of risk assessment, acceptability of evaluation results, selection of inspection methods, applicability evaluation, third-party inspection, personnel inspection management, inspection equipment status, equipment maintenance status, emergency plan formulation status, emergency material and equipment status, professionalism of emergency rescue teams, emergency drills and accident handling.

[0119] The importance of the 5 primary indicators and 16 secondary evaluation indicators in the implementation process was ranked to determine the importance of each indicator element, i.e., ranking level i. For example, when ranking the importance of the 5 primary indicators, a higher ranking indicates greater importance, and indicators with the same ranking have the same importance. Table 4-9 shows the ranking results of one expert on the primary and secondary indicators.

[0120] Table 4 Ranking Results of Primary Indicators

[0121] Indicator Name Data collection Risk assessment Integrity assessment Maintenance and Decision Emergency Management Queue levels 2 1 1 3 3

[0122] Table 5. Ranking results of secondary indicators from data collection.

[0123] Indicator Name Completeness of enterprise information Accuracy of boiler data Completeness of boiler data Queue levels 3 1 2

[0124] Table 6 Ranking Results of Secondary Indicators in Risk Assessment

[0125] Indicator Name Selection of evaluation methods Acceptability of risk assessment results Risk assessment coverage Queue levels 3 2 1

[0126] Table 7. Ranking results of the secondary indicators for integrity assessment.

[0127] Indicator Name Selection of testing methods Third-party inspection Applicability evaluation Queue levels 2 3 1

[0128] Table 8 Ranking Results of Secondary Indicators for Maintenance and Decision-Making

[0129] Indicator Name Personnel Inspection Management Inspection equipment status Equipment maintenance status Queue levels 2 1 3

[0130] Table 9 Ranking Results of Secondary Indicators for Emergency Management

[0131] Indicator Name Emergency response plan development status Emergency supplies and equipment status The professionalism of emergency rescue teams Emergency Drills and Accident Handling Queue levels 2 1 4 3

[0132] Using queuing theory, the weights of 5 primary indicators and 16 secondary evaluation indicators were determined. After normalizing the weights, they were multiplied by 100 to obtain the scoring criteria for each integrity management process indicator, as shown in Table 10.

[0133] Table 10 Scoring Criteria for Each Integrity Management Process Indicator

[0134]

[0135] Referring to Table 9, scores are assigned based on the company's actual situation to obtain the actual scores of the integrity management process indicators. The management process score is calculated and shown in Table 11.

[0136] Table 11 Actual Scores and Management Process Scores for Each Integrity Management Process Indicator

[0137]

[0138] (2) The effectiveness indicators of integrity management include input indicators and output indicators. The average inspection cost per person, the average maintenance cost per person, and the number of emergency rescue team members for each enterprise are used as input indicators, and the work efficiency, normal start-up rate, and completion rate are used as output indicators. Input indicator matrix and output indicator matrix are established respectively.

[0139] Evaluating companies using the DEA method, for example:

[0140] Table 12 Indicators and Scores of Integrity Management Effectiveness for Each Enterprise

[0141]

[0142] The DEA model corresponding to Company A is: minθ

[0143] Solve the following linear programming problem:

[0144]

[0145] The solution yields a minimum θ of 0.9734 for company A, indicating that company A's efficiency value is 0.9734 and its integrity performance score is 97.34.

[0146] Similarly, the minθ corresponding to company B is found to be 0.9688, that is, the efficiency value of company B is 0.9688, and the integrity effect score of company B is 96.88.

[0147] Neither companies A nor B experienced any accidents during the assessment period, and company C had a score of 1.

[0148] The final overall management effectiveness score is calculated using the following formula:

[0149]

[0150] Where D is the enterprise's overall management effectiveness score, D1 is the enterprise's management process score, D2 is the enterprise's management effect score, and C is the consequence compensation coefficient.

[0151] Table 12 Enterprise Scores

[0152] Company Name Management process score Management effectiveness score Consequence compensation coefficient Overall management effectiveness score Company A 60 97.34 1 78.67 Company B 59 96.88 1 77.94

[0153] Based on the final comprehensive management effectiveness score, the enterprise's comprehensive management effectiveness level is determined to be B.

Claims

1. A digital integrity management system for power plant boilers, characterized in that, The system includes: Enterprise data center module, used to store and collect enterprise information; The boiler data center module is used to store and collect historical information on all power plant boilers in the enterprise. The pressure-bearing component risk assessment module is used to evaluate the risk value and risk level of pressure-bearing components; The pressure-bearing component integrity evaluation module is used to assess the integrity status of pressure-bearing components; The maintenance and decision-making module is used to formulate maintenance strategies for components; The emergency management module is used to store and collect emergency management-related documents for the enterprise. The security knowledge base module is used to store and collect relevant laws, regulations, industry standards, and local standards. The performance evaluation module is used to evaluate the management effectiveness of enterprises; The large-screen display module intuitively displays important boiler data for later enterprise monitoring. Each module achieves dynamic closed-loop data interaction through data ports.

2. A method for evaluating the effectiveness of digital integrity management of power plant boilers, characterized in that, The digital integrity management system for power plant boilers as described in claim 1 includes the following steps: S1. Establish an efficiency evaluation index system for the digital integrity management of power plant boilers from two dimensions: management process and management effect. S2, use queuing theory to determine the weights of each indicator in the management process and calculate the management process score; S3. Use data envelopment analysis to obtain management effectiveness values ​​and calculate management performance scores. S4, determine the consequence compensation coefficient based on the severity of accidents that occur to the company during the assessment period; S5 calculates the final comprehensive management effectiveness score using management process score, management effect score, and consequence compensation coefficient, and classifies the level based on the final comprehensive management effectiveness score.

3. The method for evaluating the effectiveness of digital integrity management of power plant boilers according to claim 2, characterized in that, In S1, the power plant boiler management efficiency evaluation index system includes integrity management process indicators and integrity management effect indicators; the integrity management process indicators include data collection, risk assessment, integrity assessment, maintenance and decision-making, and emergency management; the integrity management effect indicators include input indicators and output indicators; the input indicators include per capita inspection cost, per capita maintenance cost, and number of emergency rescue team members; the output indicators include work efficiency, normal start-up rate, and completion rate.

4. The method for evaluating the effectiveness of digital integrity management of power plant boilers according to claim 2, characterized in that, S2 includes the following steps: S2-1: Rank the importance of the integrity management process indicators; S2-2: Using queuing theory, calculate the weights of each integrity management process indicator. The calculation method is as follows: In the formula, ω i Let i be the weight of each integrity management process indicator, i be the ranking value, and n be the number of integrity management process indicators. S2-3: ω i After normalization, we get S2-4: Calculate the scoring criteria for each integrity management process indicator. The calculation formula is as follows: S2-5: n experts will score each item according to the company's actual situation and the scoring criteria, and the average score will be used as the actual score for the corresponding integrity management process indicator. The management process score will be calculated using the following formula: Where D1 is the management process score, n is the number of integrity management process indicators, and x i Let x′ be the scoring criterion for the i-th integrity management process indicator. i This represents the actual score of the i-th integrity management process indicator.

5. The method for evaluating the effectiveness of digital integrity management of power plant boilers according to claim 2, characterized in that, S3 includes the following steps: S3-1: Based on the integrity management effectiveness index values, establish an input matrix X and an output matrix Y, where there are n enterprises that need to be evaluated, and each enterprise has m input indicators and s output indicators. S3-2: Using the DEA method, evaluate the j-th firm and solve for its efficiency value θ. For ease of calculation, it is transformed into an equivalent linear programming model: Where, x j =(x 1j ,x 2j ,…,x mj ) represents the input indicator value of the j-th enterprise; y j =(y 1j ,y 2j ,…,y sj ) represents the output indicator value of the j-th firm; u represents the weight of the input indicator; v represents the weight of the output indicator; λ j S is a parameter. + S - Let θ be a slack variable, and let θ represent the relative effectiveness of the j-th firm, i.e., the efficiency value of the j-th firm. S3-3: Calculate the management effectiveness score. The calculation formula is as follows: D2=θ×100 Where D2 is the management effectiveness score and θ is the enterprise's efficiency value.

6. The method for evaluating the effectiveness of digital integrity management of power plant boilers according to claim 2, characterized in that, In S4, the consequence compensation coefficient is:

7. The method for evaluating the effectiveness of digital integrity management of power plant boilers according to claim 2, characterized in that, In S5, the final comprehensive management effectiveness score is calculated using the following formula: Where D is the overall management effectiveness score, D1 is the management process score, D2 is the management effect score, and C is the consequence compensation coefficient.

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