Equipment operation state processing method and device, equipment, medium and product

Abstract

The invention discloses an equipment operation state processing method and device, equipment, a medium and a product. The method comprises the following steps: if it is detected that current time meets an evaluation period condition preset for an equipment class, obtaining a period measured value of the equipment class under each preset evaluation index from a data table through a configured data extraction rule; the evaluation indexes cover the five fields of power generation health, equipment fault, state monitoring, reliability management and experience feedback; determining an actual score and a color grade of each evaluation index of the equipment class according to a pre-configured total score of the evaluation indexes, a scoring criterion of the evaluation indexes and a periodic measured value; determining the total score of the operation state of the equipment class according to the actual scores of all the evaluation indexes under the equipment class; and generating a structured equipment class health evaluation report based on the operation state total score of the equipment class, the actual score of each evaluation index and the color grade. The embodiment of the invention can improve the equipment operation management efficiency and the unit operation reliability.

Description

Technical Field

[0001] This invention relates to the field of nuclear power plant equipment reliability management technology, and in particular to a method, apparatus, equipment, medium and product for processing equipment operating status. Background Technology

[0002] As nuclear power units age, equipment aging and potential failures increase. Traditional scheduled maintenance is inefficient and costly, necessitating predictive maintenance through equipment health assessments. Currently, nuclear power equipment health management is still conducted offline, with responsible engineers compiling a list of equipment for health management, regularly assessing and updating health status, and preparing equipment health reports. Changing the responsible engineer can lead to inconsistencies in the equipment list, resulting in inaccurate assessments of equipment health status. Regular assessments and report preparation require manual data collection from various systems and compilation into a single text document. This is labor-intensive, prone to inconsistencies in data entry, and requires accessing third-party systems or text documents for each query, consuming significant manpower and time, increasing workload, and reducing timeliness and accuracy. Summary of the Invention

[0003] This invention provides a method, apparatus, equipment, medium, and product for processing equipment operating status, so as to achieve standardized and intelligent management of equipment operating status, and realize the automatic extraction, analysis, calculation, and rapid generation of equipment health assessment data and equipment evaluation reports.

[0004] According to one aspect of the present invention, a method for processing device operating status is provided, comprising:

[0005] If the current time is detected to meet the preset evaluation cycle conditions for the equipment class, the measured values ​​of the equipment class under each preset evaluation index are obtained from the data platform through configurable data extraction rules; the evaluation index covers five major areas: power generation health, equipment failure, condition monitoring, reliability management and experience feedback.

[0006] Based on the total score of the pre-configured evaluation indicators, the scoring criteria of the evaluation indicators, and the periodic measured values, determine the actual score and color grade of each evaluation indicator for the equipment category;

[0007] The total operating status score of the equipment category is determined based on the actual scores of all evaluation indicators under the equipment category;

[0008] Based on the total operating status score of the equipment category, the actual scores of each evaluation indicator, and the color level, a structured equipment category health evaluation report is generated; the report includes at least a health scorecard, abnormal indicator analysis, and maintenance strategy optimization suggestions.

[0009] According to another aspect of the present invention, a device operation status processing apparatus is provided, comprising:

[0010] The measured value determination module is used to obtain the periodic measured values ​​of the equipment class under each preset evaluation index from the data platform through configurable data extraction rules if the current time is detected to meet the preset evaluation cycle conditions for the equipment class. The evaluation index covers five major areas: power generation health, equipment failure, condition monitoring, reliability management, and experience feedback.

[0011] The indicator score determination module is used to determine the actual score and color level of each evaluation indicator for equipment based on the pre-configured total score of the evaluation indicators, the scoring criteria of the evaluation indicators, and the periodic measured values.

[0012] The status total score determination module is used to determine the total operating status score of the equipment class based on the actual scores of all evaluation indicators under the equipment class;

[0013] The report generation module is used to generate a structured health evaluation report for the equipment class based on the total operating status score, the actual scores of each evaluation indicator, and the color level. The report includes at least a health scorecard, abnormal indicator analysis, and maintenance strategy optimization suggestions.

[0014] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the device operation state processing method according to any embodiment of the present invention.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the device operation state processing method according to any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the device operation state processing method according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer program product is provided, comprising a computer program / instructions that, when executed by a processor, implement the device operation state processing method as described in any embodiment of the present invention.

[0019] This invention establishes an automated triggering mechanism based on evaluation cycles, combined with configurable data extraction and a multi-dimensional evaluation index system, to achieve standardized quantitative evaluation of equipment health status and automatic generation of structured reports. This effectively solves the problems of inconsistent evaluation standards, low data collection efficiency, and long report compilation cycles caused by traditional reliance on manual experience, significantly improving the timeliness and accuracy of equipment status evaluation. At the same time, through the automatic identification of abnormal indicators and intelligent maintenance strategy suggestions, it provides full-process technical support for equipment reliability management, from status monitoring and problem diagnosis to decision support, ultimately achieving a dual improvement in equipment management efficiency and unit operation reliability.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a first flowchart of a device operation status processing method provided in an embodiment of the present invention;

[0023] Figure 2 This is a second flowchart of a device operation status processing method provided in an embodiment of the present invention;

[0024] Figure 3 This is a schematic diagram of the structure of a device for processing the operating status of an instrument provided in an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of the structure of an electronic device that implements an embodiment of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] Figure 1 This is a first flowchart of a device operation status processing method provided in an embodiment of the present invention. This embodiment is applicable to the standardized and intelligent management of device operation status, enabling automatic extraction, analysis, calculation, and rapid generation of device health assessment data, integrating dispersed management activities into an automated, standardized, and visualized closed-loop management system. This method can be executed by a device operation status processing device, which can be implemented in hardware and / or software and can be configured in an electronic device with corresponding data processing capabilities. Figure 1 As shown, the method includes:

[0029] S110. If the current time is detected to meet the preset evaluation cycle conditions for the device class, the measured values ​​of the device class under each preset evaluation index are obtained from the data platform through the configurable data extraction rules.

[0030] The evaluation cycle can be preset, such as monthly, quarterly, semi-annually, or annually. When the preset evaluation cycle is reached, the equipment operation status processing method will be automatically triggered.

[0031] Equipment categories refer to logical grouping units used for equipment reliability management. Multiple physical devices with the same or similar functions are grouped together as a single management object to achieve standardized health status assessments. Equipment categories include: pneumatic valves, electric valves, main coolant pumps, medium-pressure motors, main pump frequency converters, vibration instruments, nuclear safety-grade pressure / differential pressure transmitters, large rotating machinery, heat exchangers, steam turbines, circuit breakers, generators, and large power transformers, etc. Nuclear power systems have a wide variety of highly interconnected equipment; categorized management allows for clear prioritization and a focus on controlling core risks.

[0032] Optionally, a visual relationship maintenance interface can be used to maintain the mapping configuration relationships between generating units, equipment classes, and physical devices, and persistently store them in the equipment class basic information database; multi-source data related to equipment operating status can be obtained from third-party business systems and stored in the data platform; among them, third-party business systems include: real-time information system, operating restriction condition business system, status reporting system, power plant equipment implementation status system, production management system, and group experience feedback system.

[0033] The generating unit comprises various equipment categories, each containing multiple physical devices. Pre-defined evaluation indicators are established for each equipment category, covering five major areas: power generation health, equipment failure, condition monitoring, reliability management, and experience feedback. Specifically, the power generation health area includes: power loss and the number of times unplanned operational restrictions are encountered; the equipment failure area includes: the number of failures affecting equipment design functions; the condition monitoring area includes: the number of times equipment parameters are abnormal; the reliability management area includes: the number of failures or degradations of critical and sensitive equipment, the backlog of key technical issues, the backlog of production non-conformities, and the backlog of equipment changes / item replacements; and the experience feedback area includes: the backlog of work orders and the backlog of experience feedback pending implementation.

[0034] Among them, power loss refers to unplanned power loss caused by equipment problems. Number of unplanned entry into operating restriction conditions (LCO) refers to the number of times the operating restriction condition (LCO) was entered unplanned due to equipment problems. Number of failures affecting equipment design functions refers to the number of failures affecting the design functions of the equipment. Number of abnormal equipment parameters refers to the number of times abnormal equipment parameters or parameters exceeding warning values ​​were detected during equipment status monitoring. Number of failures or downgrades of critical sensitive equipment refers to the number of times critical sensitive equipment (SPV) lost function, was downgraded to other levels, or failed; equipment levels include SPV (critical sensitive equipment), NC (critical equipment), and RTM (general equipment). Inventory of key technical issues refers to the number of unclosed TOP10, medium-to-long-term, and unexplained equipment technical issues. The TOP10 refers to technical issues of high concern to the power plant and requiring key resource coordination; medium-to-long-term refers to legacy defects affecting the safety, economy, and reliability of the unit, categorized into short-term, medium-term, long-term issues, and minor defects based on the processing cycle and the degree of impact on the safe operation of the unit; unexplained equipment technical issues refer to problems that have not been clearly and accurately identified. Production Non-Conformities (NCRs) Inventory: This refers to the number of unclosed NCRs. Equipment Change / Item Replacement Inventory: This refers to the number of unclosed equipment changes / item replacements. Equipment change refers to the replacement of a component of equipment, while item replacement refers to the replacement of equipment with the same function. Backlog of Work Orders: This refers to the number of unclosed Level 4 or higher equipment CR / CM work orders. CR work orders refer to any type of equipment-related problem discovered on-site, while CM work orders refer to corrective maintenance work orders after the problem has been fixed. Pending Experience Feedback Inventory: This refers to the number of unclosed equipment-related internal / external experience feedbacks.

[0035] The real-time information system records real-time data from various monitoring points within the power plant, with some data sourced from the plant's main control system, and is used to acquire power loss data. The operational restriction condition system records operational data deviating from the technical specifications, and is used to acquire the number of unplanned entries into operational restriction conditions. The status reporting system records equipment defects and conditions within the power plant, and is used to acquire the number of failures affecting equipment design functionality. The power plant equipment implementation status system records the real-time operating status of all equipment in the power plant, and is used to acquire the number of abnormal equipment parameters. The production management system is used to acquire data on the number of failures or degradations of critical and sensitive equipment, the backlog of key technical issues, the backlog of production non-conformities, the backlog of equipment changes / item substitutions, and the backlog of work orders. The group's experience feedback system records power plant operational experience, and is used to acquire the backlog of experience feedback awaiting implementation.

[0036] By integrating multiple core business systems into a unified data platform and building a visualized interface for configuring equipment relationships and assessment rules, the entire process from data collection and status assessment to periodic triggering has been automated and intelligent. This not only breaks down traditional data silos, ensuring the comprehensiveness and accuracy of assessment data, but also, due to its highly configurable nature, possesses strong adaptability and scalability, enabling flexible responses to changes in business rules and data sources. This significantly improves the efficiency of nuclear power plant equipment reliability management, the scientific nature of decision-making, and the long-term maintainability of the system.

[0037] Data related to equipment operating status is obtained from third-party business systems, including status reports, LCO operating limits, work orders, NCR non-compliance items, internal / external experience feedback, SPV (critical sensitive equipment) failures and degradations, and medium- to long-term technical issues. This multi-source data is then extracted, cleaned, and transformed before being stored in a data platform. If the current time meets the preset evaluation cycle conditions for a particular equipment category, the measured values ​​for that category under various preset evaluation indicators are retrieved from the data platform using configurable data extraction rules.

[0038] Optionally, the step of obtaining the periodic measured values ​​of the device class under each preset evaluation index from the data platform through configurable data extraction rules includes: pre-setting the mapping relationship between each evaluation index and a specific data source in the data platform, and obtaining the periodic measured values ​​of the device class under the evaluation index from the data platform according to the mapping relationship.

[0039] Optionally, a separate structured query statement can be configured for each evaluation indicator through a visual interface to obtain the periodic measured values ​​of the equipment class under the evaluation indicator from the data platform.

[0040] By predefined mapping relationships between evaluation metrics and data sources, and through a visual interface to configure independent structured query statements, flexible configuration and efficient automation of evaluation data collection are achieved. This enhances the system's adaptability to different data sources and changes in business rules, avoids modifications to the core system code due to changes in the underlying data structure, thereby significantly reducing maintenance costs and ensuring the continuity and stability of the equipment status evaluation process.

[0041] S120. Based on the total score of the pre-configured evaluation indicators, the scoring criteria of the evaluation indicators, and the periodic measured values, determine the actual score and color grade of each evaluation indicator for the equipment category.

[0042] The total score and scoring criteria of each evaluation indicator are pre-configured; based on the total score, scoring criteria and the periodic measured value of the equipment category in the current period, the actual score of each evaluation indicator of the equipment category is determined, and the health color level of the equipment category under the corresponding evaluation indicator is determined according to the actual score of the evaluation indicator and the preset color mapping relationship.

[0043] S130. Determine the total operating status score of the equipment category based on the actual scores of all evaluation indicators under the equipment category.

[0044] The total operating status score of the equipment class is obtained by summing the actual scores of all evaluation indicators under the same equipment class.

[0045] S140. Based on the total operating status score of the equipment category, the actual score of each evaluation indicator, and the color level, generate a structured equipment category health evaluation report.

[0046] The report should include at least a health scorecard, analysis of abnormal indicators, and recommendations for optimizing maintenance strategies.

[0047] Based on the total operating status score of equipment, the actual scores of each evaluation indicator, and the color level, a structured equipment health evaluation report is generated, which includes a health scorecard, anomaly indicator analysis, and maintenance strategy optimization suggestions. The health scorecard intuitively displays the overall health status of the equipment and each indicator through quantitative scores and color coding. The anomaly indicator analysis automatically identifies and focuses on anomaly indicators based on color levels to trace the root causes and analyze their impact. The maintenance strategy optimization suggestions generate targeted maintenance priority ranking, resource allocation plans, and preventive maintenance recommendations based on the anomaly analysis results, thus forming a complete closed loop from status assessment and anomaly diagnosis to maintenance decision-making, significantly improving the transparency of equipment status and the efficiency of operation and maintenance decision-making.

[0048] Equipment information marked as having abnormal health conditions in the health assessment report will be sent to the power plant health management committee so that the company's management can make decisions and formulate corrective measures for the equipment's health.

[0049] This invention establishes an automated triggering mechanism based on evaluation cycles, combined with configurable data extraction and a multi-dimensional evaluation index system, to achieve standardized quantitative evaluation of equipment health status and automatic generation of structured reports. This effectively solves the problems of inconsistent evaluation standards, low data collection efficiency, and long report compilation cycles caused by traditional reliance on manual experience, significantly improving the timeliness and accuracy of equipment status evaluation. At the same time, through the automatic identification of abnormal indicators and intelligent maintenance strategy suggestions, it provides full-process technical support for equipment reliability management, from status monitoring and problem diagnosis to decision support, ultimately achieving a dual improvement in equipment management efficiency and unit operation reliability.

[0050] Figure 2 This is a second flowchart of a device operation status processing method provided in an embodiment of the present invention. This embodiment is an optimization and improvement based on the above embodiment. Figure 2 As shown, the method includes:

[0051] S210. If the current time is detected to meet the preset evaluation cycle conditions for the device class, the measured values ​​of the device class under each preset evaluation index are obtained from the data platform through the configurable data extraction rules.

[0052] The assessment indicators cover five major areas: power generation health, equipment failure, condition monitoring, reliability management, and experience feedback.

[0053] S220. Determine the score rate and color grade of the equipment category under the evaluation index based on the scoring criteria and the measured values ​​of the period.

[0054] S230. Determine the actual score of the equipment category under the evaluation indicators based on the total score of the evaluation indicators and the score rate.

[0055] The scoring criteria include a binary judgment criterion based on a preset threshold and a multi-level judgment criterion. The binary judgment criterion is applicable to the evaluation indicators in the field of power generation health, including a score rate of 100% when the periodic measured value is better than the preset threshold and a score rate of zero when it is worse than or equal to the preset threshold. The multi-level judgment criterion is applicable to the evaluation indicators in the fields of equipment failure, condition monitoring, reliability management and experience feedback, including mapping different score rates according to different quantity ranges of the periodic measured value.

[0056] For example, the total score of the preset power loss assessment index is 15; a binary judgment criterion based on a preset threshold is adopted, specifically: if the power generation loss is less than 500MWHr, the score rate is 100% and the color level is green; if the power generation loss is greater than or equal to 500MWHr, the score rate is 0 and the color level is red.

[0057] The total score for the evaluation index of the number of unplanned entry into the operation restriction conditions is 15. A binary judgment criterion with preset thresholds is adopted. Specifically, if the number of unplanned entry into the operation restriction conditions is 0, the score rate is 100% and the color level is green; if the number of unplanned entry into the operation restriction conditions is greater than or equal to 1, the score rate is 0 and the color level is red.

[0058] The total score for the evaluation index of the number of failures affecting the equipment's design function is 12. A multi-level judgment criterion is adopted, specifically: if the number of failures affecting the equipment's design function is 0, the score rate is 100% and the color level is green; if the number of failures affecting the equipment's design function is 1 or 2, the score rate is 75% and the color level is white; if the number of failures affecting the equipment's design function is 3 or 4, the score rate is 50% and the color level is yellow; if the number of failures affecting the equipment's design function is greater than or equal to 5, the score rate is 0 and the color level is red.

[0059] The total score for the equipment parameter anomaly frequency assessment index is 12. A multi-level judgment criterion is adopted, specifically: if the number of equipment parameter anomalies is 0, the score rate is 100% and the color level is green; if the number of equipment parameter anomalies is 1-2, the score rate is 75% and the color level is white; if the number of equipment parameter anomalies is 3-4, the score rate is 50% and the color level is yellow; if the number of equipment parameter anomalies is 5 or more, the score rate is 0 and the color level is red.

[0060] The total score for the evaluation index of the number of failures or downgrades of critical sensitive equipment is 18. A multi-level judgment criterion is adopted, specifically: if the number of failures or downgrades of critical sensitive equipment is 0, the score rate is 100% and the color level is green; if the number of failures or downgrades of critical sensitive equipment is 1-2, the score rate is 75% and the color level is white; if the number of failures or downgrades of critical sensitive equipment is 3-4, the score rate is 50% and the color level is yellow; if the number of failures or downgrades of critical sensitive equipment is 5 or more, the score rate is 0 and the color level is red.

[0061] The total score for the assessment indicators of key technical issues is 18. A multi-level judgment criterion is adopted, specifically: if there are 0 key technical issues, the score rate is 100% and the color level is green; if there are 1 or 2 key technical issues, the score rate is 75% and the color level is white; if there are 3 or 4 key technical issues, the score rate is 50% and the color level is yellow; if there are 5 or more key technical issues, the score rate is 0 and the color level is red.

[0062] The total score for the production non-conformity inventory assessment index is 10. A multi-level judgment criterion is adopted, specifically: if there are 0 production non-conformities, the score rate is 100% and the color level is green; if there are 1 or 2 production non-conformities, the score rate is 75% and the color level is white; if there are 3 or 4 production non-conformities, the score rate is 50% and the color level is yellow; if there are 5 or more production non-conformities, the score rate is 0 and the color level is red.

[0063] The total score for the equipment change / item replacement stock assessment index is 10. A multi-level judgment criterion is adopted, specifically: if there are 0 equipment changes / item replacements, the score rate is 100% and the color level is green; if there are 1 or 2 equipment changes / item replacements, the score rate is 75% and the color level is white; if there are 3 or 4 equipment changes / item replacements, the score rate is 50% and the color level is yellow; if there are 5 or more equipment changes / item replacements, the score rate is 0 and the color level is red.

[0064] The total score for the backlog of work orders assessment index is 10. A multi-level judgment criterion is adopted, specifically: if the backlog of work orders is 0, the score rate is 100% and the color level is green; if the backlog of work orders is 1-3, the score rate is 75% and the color level is white; if the backlog of work orders is 4-6, the score rate is 50% and the color level is yellow; if the backlog of work orders is 7 or more, the score rate is 0 and the color level is red.

[0065] The total score for the assessment indicator of the backlog of experience feedback to be implemented is 10. A multi-level judgment criterion is adopted, specifically: if there are 0 backlogs of experience feedback to be implemented, the score rate is 100% and the color level is green; if there are 1-2 backlogs of experience feedback to be implemented, the score rate is 75% and the color level is white; if there are 3-4 backlogs of experience feedback to be implemented, the score rate is 50% and the color level is yellow; if there are 5 or more backlogs of experience feedback to be implemented, the score rate is 0 and the color level is red.

[0066] The score rate and color grade of the equipment category under the evaluation indicators are determined based on the scoring criteria and periodic measured values; the product of the total score of the evaluation indicators and the score rate is calculated to determine the actual score of the equipment category under the evaluation indicators.

[0067] S240. Determine the total operating status score of the equipment category based on the actual scores of all evaluation indicators under the equipment category.

[0068] S250. Based on the total operating status score of the equipment category, the actual score of each evaluation indicator, and the color level, generate a structured equipment category health evaluation report.

[0069] The report should include at least a health scorecard, analysis of abnormal indicators, and recommendations for optimizing maintenance strategies.

[0070] Optionally, generating a structured equipment health evaluation report based on the total operating status score of the equipment category, the actual scores of each evaluation indicator, and the color level includes: setting an overall color level identifier for the equipment health evaluation report based on the total operating status score of the equipment category; and setting a corresponding color level identifier for each evaluation indicator of the equipment category based on the actual scores and color levels of each evaluation indicator; wherein the color level identifier includes at least one of green, white, yellow, and red, corresponding to healthy, slightly concerning, moderately concerning, and severely abnormal equipment statuses, respectively.

[0071] Based on the color level, fill in the content in the corresponding module of the report. When the overall color level of the equipment is green, the report conclusion can be set to "The health status of the equipment is acceptable, and reliability is maintained according to normal procedures". When the color level of any indicator is white, yellow or red, the corresponding tracking and analysis items are generated in the abnormal indicator analysis and maintenance strategy optimization suggestion section of the report.

[0072] By automatically mapping the total score of equipment operating status and the actual scores of each evaluation indicator to multi-level color labels such as green, white, yellow, and red, an intuitive and visual presentation of equipment health status is achieved. This enables managers to quickly identify the overall equipment health level and specific abnormal indicators, significantly improving the efficiency of status monitoring. Through the precise correspondence between color levels and status levels such as healthy, slightly concerned, moderately concerned, and seriously abnormal, a clear basis is provided for the graded handling of anomalies and the priority allocation of maintenance resources. This effectively promotes the transformation of equipment management from passive response to proactive prevention, and ultimately builds a standardized, timely, and efficient visual management and control mechanism for equipment health status.

[0073] Optionally, after determining the total operating status score of the equipment class based on the actual scores of all evaluation indicators under the equipment class, the method further includes: generating a visual analysis view, which includes a horizontal comparison view of the units and a vertical analysis view of the equipment; wherein, the horizontal comparison view of the units is used to visually compare and display the overall health scores of different units; the overall health score of the units is obtained by summarizing the total operating status scores of all equipment classes under the units; the vertical analysis view of the equipment is used to visually compare and analyze the health indicators of each physical device under the same equipment class.

[0074] Health indicators for physical equipment include: the number of failures affecting the equipment's design function, the backlog of work orders, the inventory of equipment changes / item replacements, the inventory of experience feedback pending implementation, the inventory of production non-conformities, and the number of times equipment parameters are abnormal.

[0075] By generating horizontal comparison views of generating units and vertical analysis views of equipment, a multi-dimensional equipment health data analysis system was constructed. The horizontal comparison view summarizes and displays the overall health scores of different generating units, enabling managers to quickly identify reliability differences between units and providing a basis for resource coordination and macro-level decision-making. The vertical analysis view compares the health indicators of various physical devices within the same equipment category, accurately pinpointing weak points in similar equipment and enabling fault warnings and differentiated maintenance. This combined horizontal and vertical visualization analysis mode overcomes the limitations of traditional single-equipment assessments, forming a complete insight chain from macro-level unit management to micro-level equipment diagnosis, thus improving the systematicness and accuracy of equipment reliability management.

[0076] This invention establishes an automated triggering mechanism and configurable data acquisition process based on an evaluation cycle. Combined with an evaluation index system covering five major areas—power generation health, equipment failure, condition monitoring, reliability management, and experience feedback—it employs a scientific scoring criterion that combines binary and multi-level judgments. This automatically converts equipment operating data into quantitative scores and multi-level color-coded labels, ultimately generating a structured evaluation report containing health scorecards, anomaly indicator analysis, and maintenance strategy optimization suggestions. This achieves standardization and automation of the entire process of equipment health status assessment, from data collection and quantitative evaluation to decision-making recommendations. It effectively solves the problems of low efficiency, poor consistency, and insufficient decision-making basis inherent in traditional manual assessments, significantly improving the accuracy of equipment condition perception, the speed of operation and maintenance response, and the scientific nature of management decisions.

[0077] Figure 3 This is a schematic diagram of the structure of a device for processing the operating status of an instrument provided in an embodiment of the present invention. Figure 3 As shown, the device includes:

[0078] The measured value determination module 310 is used to obtain the periodic measured values ​​of the equipment class under each preset evaluation index from the data platform through configurable data extraction rules if the current time is detected to meet the preset evaluation cycle conditions for the equipment class. The evaluation index covers five major areas: power generation health, equipment failure, status monitoring, reliability management and experience feedback.

[0079] The indicator score determination module 320 is used to determine the actual score and color level of each evaluation indicator for equipment based on the pre-configured total score of the evaluation indicators, the scoring criteria of the evaluation indicators, and the periodic measured values.

[0080] The status total score determination module 330 is used to determine the total operating status score of the equipment class based on the actual scores of all evaluation indicators under the equipment class;

[0081] The report generation module 340 is used to generate a structured equipment health evaluation report based on the total operating status score of the equipment class, the actual scores of each evaluation indicator, and the color level; the report includes at least a health scorecard, abnormal indicator analysis, and maintenance strategy optimization suggestions.

[0082] The device operation status processing apparatus provided in the embodiments of the present invention can execute the device operation status processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0083] Optionally, the indicator score determination module is specifically used for: determining the score rate of the equipment class under the evaluation indicators based on the scoring criteria and the periodic measured values; determining the actual score of the equipment class under the evaluation indicators based on the total score of the evaluation indicators and the score rate; wherein, the scoring criteria include a binary judgment criterion based on a preset threshold and a multi-level judgment criterion; the binary judgment criterion is applicable to evaluation indicators in the field of power generation health, including a score rate of 100% when the periodic measured values ​​are better than the preset threshold and a score rate of zero when they are worse than or equal to the preset threshold; the multi-level judgment criterion is applicable to evaluation indicators in the fields of equipment failure, condition monitoring, reliability management, and experience feedback, including mapping different score rates according to different quantity ranges of the periodic measured values.

[0084] Optionally, the report generation module is specifically used to: set an overall color level identifier for the equipment category health evaluation report based on the total operating status score of the equipment category; and set a corresponding color level identifier for each evaluation indicator of the equipment category based on the actual score and color level of each evaluation indicator; wherein the color level identifier includes at least one of green, white, yellow and red, corresponding to the equipment status of healthy, slightly concerned, moderately concerned and seriously abnormal, respectively.

[0085] Optionally, the measured value determination module is specifically used to: pre-set the mapping relationship between each evaluation indicator and a specific data source in the data platform, and obtain the periodic measured values ​​of the device class under the evaluation indicators from the data platform according to the mapping relationship.

[0086] Optionally, it also includes: an equipment organization and management module, which is used to maintain the mapping configuration relationship between units, equipment classes and physical equipment through a visual relationship maintenance interface, and persistently store it in the equipment class basic information database;

[0087] The multi-source data acquisition module is used to acquire multi-source data related to equipment operating status from third-party business systems and store it in the data platform; wherein, the third-party business systems include: real-time information system, operating restriction condition business system, status report system, power plant equipment implementation status system, production management system, and group experience feedback system.

[0088] Optionally, it also includes: a visualization view generation module, used to generate a visualization analysis view after determining the total operating status score of the equipment class based on the actual scores of all evaluation indicators under the equipment class. The view includes a horizontal comparison view of the units and a vertical analysis view of the equipment. The horizontal comparison view of the units is used to visually compare and display the overall health scores of different units. The overall health score of the units is obtained by summarizing the total operating status scores of all equipment classes under the units. The vertical analysis view of the equipment is used to visually compare and analyze the health indicators of each physical device under the same equipment class.

[0089] The device operation status processing apparatus described in further detail can also execute the device operation status processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0090] According to embodiments of the present invention, the present invention also provides an electronic device, a readable storage medium, and a computer program product.

[0091] Figure 4 A schematic diagram of an electronic device 40 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0092] like Figure 4 As shown, the electronic device 40 includes at least one processor 41 and a memory, such as a read-only memory 42 or a random access memory 43, communicatively connected to the at least one processor 41. The memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes based on the computer program stored in the read-only memory 42 or loaded from storage unit 48 into the random access memory 43. The random access memory 43 may also store various programs and data required for the operation of the electronic device 40. The processor 41, read-only memory 42, and random access memory 43 are interconnected via a bus 44. An input / output interface 45 is also connected to the bus 44.

[0093] Multiple components in electronic device 40 are connected to input / output interface 45, including: input unit 46, such as keyboard, mouse, etc.; output unit 47, such as various types of monitors, speakers, etc.; storage unit 48, such as disk, optical disk, etc.; and communication unit 49, such as network card, modem, wireless transceiver, etc. Communication unit 49 allows electronic device 40 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0094] Processor 41 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, central processing units, graphics processing units, various special-purpose artificial intelligence computing chips, various processors running machine learning model algorithms, digital signal processors, and any suitable processor, controller, microcontroller, etc. Processor 41 performs the various methods and processes described above, such as device operating state processing methods.

[0095] In some embodiments, the device operating state processing method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 40 via read-only memory 42 and / or communication unit 49. When the computer program is loaded into random access memory 43 and executed by processor 41, one or more steps of the device operating state processing method described above may be performed. Alternatively, in other embodiments, processor 41 may be configured to execute the device operating state processing method by any other suitable means (e.g., by means of firmware).

[0096] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays, application-specific integrated circuits (ASICs), application-specific standard products (ASICs), systems-on-a-chip (SoCs), payload programmable logic devices, computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0097] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0098] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory, optical fibers, portable compact disk read-only memory, optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0099] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a cathode ray tube, liquid crystal display, or monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0100] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0101] A computing system can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product within the cloud computing service system to address the shortcomings of traditional physical hosts and virtual private servers, such as high management difficulty and weak business scalability.

[0102] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and no limitation is imposed herein.

[0103] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method of handling a device operating state, characterized by, The method comprises: If it is detected that the current time meets the evaluation period condition preset for the equipment class, then the periodic measured values of the equipment class under each preset evaluation index are obtained from the data center through the configured data extraction rule; the evaluation index covers five fields of power generation health, equipment failure, state monitoring, reliability management and experience feedback; According to the total score of the pre-configured evaluation index, the scoring criteria of the evaluation index and the periodic measured value, the actual score and color level of each evaluation index of the equipment class are determined; According to the actual scores of all evaluation indexes of the equipment class, the total score of the running state of the equipment class is determined; Based on the total score of the running state of the equipment class, the actual score and color level of each evaluation index, a structured equipment class health evaluation report is generated; the report at least includes a health score card, an abnormal index analysis and a maintenance strategy optimization suggestion.

2. The method of claim 1, wherein, The actual score of each evaluation index of the equipment class is determined according to the total score of the pre-configured evaluation index, the scoring criteria of the evaluation index and the periodic measured value, which comprises: The score rate of the equipment class under the evaluation index is determined according to the scoring criteria and the periodic measured value; The actual score of the equipment class under the evaluation index is determined according to the total score of the evaluation index and the score rate; The scoring criteria include binary judgment criteria based on a preset threshold and multi-level judgment criteria; the binary judgment criteria are applicable to the evaluation index in the field of power generation health, including a score rate of 100% when the periodic measured value is better than the preset threshold, and a score rate of 0 when the periodic measured value is worse than or equal to the preset threshold; the multi-level judgment criteria are applicable to the evaluation index in the fields of equipment failure, state monitoring, reliability management and experience feedback, including different score rates according to different number intervals of the periodic measured value.

3. The method of claim 1, wherein, The structured equipment class health evaluation report is generated based on the total score of the running state of the equipment class, the actual score and color level of each evaluation index, which comprises: The overall color level identifier of the equipment class health evaluation report is set according to the total score of the running state of the equipment class; The corresponding color level identifier of each evaluation index of the equipment class is set according to the actual score and color level of each evaluation index; The color level identifier includes at least one of green, white, yellow and red, which respectively correspond to the equipment state of health, mild attention, moderate attention and serious abnormality.

4. The method of claim 1, wherein, The periodic measured value of the equipment class under each preset evaluation index is obtained from the data center through the configured data extraction rule, which comprises: The mapping relationship between each evaluation index and a specific data source in the data center is preset, and the periodic measured value of the equipment class under the evaluation index is obtained from the data center according to the mapping relationship.

5. The method of claim 1, wherein, It also comprises: The mapping configuration relationship between the unit, the equipment class and the physical equipment is maintained through the visual relationship maintenance interface, and is persistently stored in the equipment class basic information database; Obtain multi-source data related to the equipment running state from a third-party business system and store in a data center; wherein the third-party business system includes: a real-time information system, an operating limit condition business system, a state reporting system, a power plant equipment implementation status system, a production management system, and a group experience feedback system.

6. The method of claim 1, wherein, After determining the total score of the running state of the equipment class according to the actual scores of all evaluation indexes of the equipment class, the method further includes: Generating a visual analysis view, which includes a unit transverse comparison view and an equipment longitudinal analysis view; The unit transverse comparison view is used for visual comparison and display of the overall health score of different units; the overall health score of the unit is obtained by aggregating the total score of the running state of all equipment classes under the unit; the equipment longitudinal analysis view is used for visual comparison and analysis of the health indexes of each physical equipment under the same equipment class.

7. An apparatus operation state processing device, characterized by comprising: The device includes: A measured value determination module configured to, if it is detected that the current time satisfies the preset evaluation period condition of the equipment class, obtain the periodic measured values of the equipment class under each preset evaluation index from the data center through configured data extraction rules; the evaluation indexes cover five fields of power generation health, equipment failure, state monitoring, reliability management, and experience feedback; An index score determination module configured to determine the actual scores and color levels of each evaluation index of the equipment class according to the total score of the evaluation index, the scoring criteria of the evaluation index, and the periodic measured values; A state total score determination module configured to determine the total score of the running state of the equipment class according to the actual scores of all evaluation indexes of the equipment class; A report generation module configured to generate a structured equipment class health evaluation report based on the total score of the running state of the equipment class, the actual scores of each evaluation index, and the color levels; the report at least includes a health score card, an abnormal index analysis, and a maintenance strategy optimization suggestion.

8. An electronic device, comprising: The electronic device includes: At least one processor; And a memory connected in communication with the at least one processor; The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the equipment running state processing method of any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for enabling the processor to execute the equipment running state processing method of any one of claims 1-6 when executed.

10. A computer program product comprising a computer program that, when executed by a processor, implements the equipment running state processing method according to any one of claims 1-6.

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