Comprehensive state evaluation method and system for thermal power plant equipment, medium and electronic equipment

Abstract

The invention provides a comprehensive state evaluation method and system for thermal power plant equipment, a medium and electronic equipment, and relates to the technical field of equipment detection and early warning, and the method comprises the steps: obtaining preset operation parameter data, current energy efficiency and design energy efficiency indexes of current target equipment, and vibration data, determining a preset structure abnormal condition of the target equipment and a service life use condition of a preset part; based on the preset operation parameter data and the preset optimal operation parameter of the target equipment, determining a preset operation parameter deviation condition; based on the current energy efficiency and the designed energy efficiency index, the energy efficiency standard reaching condition is determined; determining a vibration change condition based on the vibration data in the preset time period; and determining the comprehensive state of the target equipment by combining the five conditions of the target equipment. According to the method and the device, the problems that the evaluation of the equipment state is relatively single, the accuracy is insufficient and the real-time performance is poor in the prior art are solved.

Description

Technical Field

[0001] This disclosure relates to the field of equipment detection and early warning technology, and in particular to a comprehensive condition assessment method, system, medium and electronic equipment for thermal power plant equipment. Background Technology

[0002] Currently, thermal power generation remains the primary mode of electricity generation. In recent years, the growth rate of thermal power generation has been 1.5%, and the installed capacity of thermal power plants has increased by 3.8% year-on-year. Despite facing competition from new energy sources and environmental pressures, thermal power generation remains the core force of electricity supply. However, the equipment in thermal power plants suffers from various instabilities, which can easily affect the stable operation of the equipment.

[0003] Against this backdrop, there is a need to find a means to assess the condition of thermal power plant equipment in order to identify potential problems in the equipment in a timely manner, improve the safety of thermal power plant equipment operation, and reduce the possibility of accidents.

[0004] However, existing equipment evaluation methods, such as non-destructive testing or thermal imaging, are relatively simple in their assessment of equipment status. When faced with the complex and ever-changing operating status of thermal power plant equipment and the difficulty in accurately detecting potential faults, these traditional evaluation methods tend to exhibit insufficient accuracy and poor real-time performance. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this disclosure provides a comprehensive condition assessment method, system, medium, and electronic equipment for thermal power plant equipment. This solves the problems of existing technologies where the assessment of equipment condition is relatively singular, easily leading to insufficient accuracy and poor real-time performance.

[0006] At least one embodiment of this disclosure provides a comprehensive condition assessment method for thermal power plant equipment, including:

[0007] Acquire the preset operating parameter data, current energy efficiency and design energy efficiency indicators of the current target equipment, as well as vibration data within a preset time period, and determine the preset structural abnormalities and lifespan of the preset components of the target equipment;

[0008] Based on the preset operating parameter data and preset optimal operating parameters of the target device, determine the deviation of the preset operating parameters of the target device;

[0009] Based on the current energy efficiency and design energy efficiency indicators, determine the energy efficiency compliance status of the target equipment;

[0010] Based on the vibration data within a preset time period, the vibration changes of the target equipment are determined;

[0011] The overall status of the target equipment is determined by combining the deviation of the preset operating parameters, the energy efficiency compliance, the vibration changes, the preset structural anomalies, and the service life.

[0012] The technical solution provided in this disclosure has at least the following beneficial effects:

[0013] This method overcomes the limitations of traditional equipment assessment methods that rely on single indicators. It integrates data from five key dimensions: the impact of operational parameters on process status, the economic impact of current energy efficiency, the mechanical health impact of vibration changes, the potential risk impact of structural anomalies, and the impact of equipment aging on lifespan. Utilizing data from these five key dimensions allows for cross-validation, significantly reducing the possibility of false alarms and missed alarms. This enables an unprecedentedly comprehensive, accurate, and quantitative assessment of the health status of critical equipment in thermal power plants. It provides highly practical and directly decision-making insights for equipment management and operational optimization, thereby effectively improving the economy, reliability, and safety of power plant operations.

[0014] In a comprehensive condition assessment method for thermal power plant equipment provided in one embodiment of this disclosure, determining the deviation of the preset operating parameters of the target equipment based on preset operating parameter data and preset optimal operating parameters includes:

[0015] The deviation of the preset operating parameters of the target device is determined according to the following formula:

[0016]

[0017] Where σ represents the deviation of the preset operating parameters, n represents the type of preset operating parameters of the target device, and x i This represents the preset operating parameter data, where μ represents the preset optimal operating parameters.

[0018] In a comprehensive condition assessment method for thermal power plant equipment provided in one embodiment of this disclosure, determining the deviation of the preset operating parameters of the target equipment based on preset operating parameter data and preset optimal operating parameters includes:

[0019] The target device includes multiple components. For each component, based on the current preset operating parameter data of the component and the preset optimal operating parameters of the component, the deviation of the preset operating parameters of the component is determined, and the initial operating state evaluation score of the component is determined according to the deviation of the preset operating parameters of the component.

[0020] By combining the initial operating status evaluation scores of each component, the deviation of the preset operating parameters of the target device is determined.

[0021] In one embodiment of this disclosure, a method for comprehensive status assessment of thermal power plant equipment includes determining the deviation of preset operating parameters of the target equipment by combining the initial operating status assessment scores of each component.

[0022] When the initial operating status evaluation score of any of the components is within a preset range, the deviation of the preset operating parameters of the target device is determined to be a preset condition.

[0023] When the initial operating status evaluation scores of all the components are outside the preset range, the deviation of the preset operating parameters of the target device is determined based on the weighted algorithm and the initial operating status evaluation scores of all the components.

[0024] In one embodiment of this disclosure, a method for comprehensive condition assessment of thermal power plant equipment includes determining the vibration changes of the target equipment based on vibration data within a preset time period, comprising:

[0025] Based on the vibration data within a preset time period, determine the initial vibration change of the target device, and determine the deviation ratio between the initial vibration change and a preset threshold.

[0026] The vibration variation of the target equipment is determined based on the deviation ratio.

[0027] In one embodiment of this disclosure, a method for comprehensive condition assessment of thermal power plant equipment includes determining the comprehensive condition of the target equipment by combining the deviation of preset operating parameters, the energy efficiency compliance status, the vibration changes, the preset structural anomalies, and the service life.

[0028] Based on the deviation of the preset operating parameters, the energy efficiency compliance, the vibration change, the preset structural anomaly, and the lifespan, the operating status score, energy efficiency status score, vibration status score, structural status score, and lifespan status score of the target equipment are determined respectively.

[0029] If at least one of the operating status score, energy efficiency score, vibration status score, structural status score, and lifespan status score falls within a preset range, the overall status of the target equipment is determined to be the preset status.

[0030] In one embodiment of this disclosure, a comprehensive condition assessment method for thermal power plant equipment is provided, the method further includes:

[0031] If the operating status score, energy efficiency score, vibration status score, structural status score, and lifespan status score are all outside the preset range, the overall status of the target equipment is determined based on a weighted algorithm, combining the operating status score, energy efficiency score, vibration status score, structural status score, and lifespan status score.

[0032] At least one embodiment of this disclosure also provides a comprehensive condition assessment system for thermal power plant equipment, comprising:

[0033] The data acquisition module acquires the preset operating parameter data, current energy efficiency and design energy efficiency indicators of the current target equipment, as well as vibration data within a preset time period, and determines the preset structural abnormalities and lifespan of the preset components of the target equipment.

[0034] The operating parameter deviation calculation module determines the deviation of the target device's preset operating parameters based on the preset operating parameter data and the preset optimal operating parameters.

[0035] The energy efficiency compliance calculation module determines the energy efficiency compliance status of the target equipment based on the current energy efficiency and the design energy efficiency index.

[0036] The vibration change calculation module determines the vibration change of the target equipment based on the vibration data within a preset time period.

[0037] The comprehensive status confirmation module determines the comprehensive status of the target equipment by combining the deviation of the preset operating parameters, the energy efficiency compliance, the vibration changes, the preset structural anomalies, and the lifespan of the target equipment.

[0038] This disclosure also provides a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to perform the comprehensive condition assessment method for thermal power plant equipment as described above.

[0039] This disclosure also provides an electronic device, including a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement the comprehensive condition assessment method for thermal power plant equipment as described above. Attached Figure Description

[0040] Figure 1 This is a flowchart illustrating the comprehensive condition assessment method for thermal power plant equipment provided in this disclosure;

[0041] Figure 2 A line graph showing the changes in vibration;

[0042] Figure 3 A schematic diagram of the integrated condition assessment system for thermal power plant equipment provided in this disclosure;

[0043] Figure 4 This is a schematic diagram of the structure of the electronic device provided in this disclosure.

[0044] The attached diagram lists the components represented by each number as follows:

[0045] 10. Electronic device; 11. Processor; 12. Read-only memory (ROM); 13. Random access memory (RAM); 14. Bus; 15. Input / output (I / O) interface; 16. Input unit; 17. Output unit; 18. Storage unit; 19. Communication unit. Detailed Implementation

[0046] The principles and features of this disclosure are described below. The examples given are for illustrative purposes only and are not intended to limit the scope of this disclosure.

[0047] This disclosure provides a comprehensive condition assessment method for thermal power plant equipment. Please refer to [link / reference here]. Figure 1 As shown, it includes:

[0048] Acquire the preset operating parameter data, current energy efficiency and design energy efficiency indicators of the current target equipment, as well as the vibration data within the preset time period, and determine the preset structural anomalies and the lifespan of the preset components of the target equipment;

[0049] Based on the preset operating parameter data and the preset optimal operating parameters of the target equipment, determine the deviation of the preset operating parameters of the target equipment;

[0050] Based on current and design energy efficiency indicators, determine the energy efficiency compliance status of the target equipment;

[0051] Based on vibration data within a preset time period, determine the vibration changes of the target equipment;

[0052] The overall status of the target equipment is determined by combining the deviation of the preset operating parameters, the compliance of energy efficiency, the changes in vibration, the pre-set structural anomalies, and the service life.

[0053] This method overcomes the limitations of traditional equipment assessment methods that rely on single indicators. It integrates data from five key dimensions: the impact of operational parameters on process status, the economic impact of current energy efficiency, the mechanical health impact of vibration changes, the potential risk impact of structural anomalies, and the impact of equipment aging on lifespan. Utilizing data from these five key dimensions allows for cross-validation, significantly reducing the possibility of false alarms and missed alarms. This enables an unprecedentedly comprehensive, accurate, and quantitative assessment of the health status of critical equipment in thermal power plants. It provides highly practical and directly decision-making insights for equipment management and operational optimization, thereby effectively improving the economy, reliability, and safety of power plant operations.

[0054] It should be understood that, in this disclosure, to facilitate a more intuitive representation of the overall status of the target device, this embodiment divides the overall status of the target device into five stages: excellent, normal, deteriorated, abnormal, and severe. Each stage has a different overall status score, and their specific relationships are shown in Table 1.

[0055] Table 1: Relationship between the overall status and score of the target equipment

[0056] Overall Status excellent normal Deterioration abnormal serious Score 90-100 75-90 65-75 55-65 <55

[0057] Specifically, the above-mentioned acquisition of the target equipment's preset operating parameter data, current energy efficiency and design energy efficiency indicators, and vibration data within a preset time period, as well as the determination of the target equipment's preset structural anomalies and preset component lifespan, can all be obtained through the following information:

[0058] 1. Pre-commissioning information: This mainly includes the equipment's technical specifications, factory test reports, acceptance records, installation and acceptance records, and relevant structural drawings and other related information;

[0059] 2. Operational information: This mainly includes data information obtained from the Distributed Control System (DCS) or the Supervisory Information System in Plant (SIS) and related online monitoring systems.

[0060] 3. Inspection information: This mainly includes equipment inspection records, maintenance records, fault records, defect and troubleshooting records, etc.

[0061] 4. Maintenance and testing information: This mainly includes routine test reports, diagnostic test reports, maintenance reports, and equipment modification reports.

[0062] 5. Other information: This mainly includes information on similar equipment failures, family defects, and the failure to implement relevant accident prevention measures.

[0063] In one exemplary embodiment provided in this disclosure, determining the deviation of the target device's preset operating parameters based on preset operating parameter data and preset optimal operating parameters includes:

[0064] The target device includes multiple components. For each component, based on the current component's preset operating parameter data and the component's preset optimal operating parameters, the deviation of the component's preset operating parameters is determined, and based on the deviation of the component's preset operating parameters, the component's initial operating status evaluation score is determined.

[0065] By combining the initial operating status evaluation scores of each component, the deviation of the target equipment's preset operating parameters is determined.

[0066] Specifically, based on the current preset operating parameter data of the component and the component's preset optimal operating parameters, the deviation of the component's preset operating parameters is determined, including:

[0067] First, based on the preset operating parameter data of each component, determine the preset optimal operating parameters of each component according to the following formula:

[0068]

[0069] Where μ represents the preset optimal operating parameters, x i This represents the preset operating parameter data within a preset time period, where n represents the type of preset operating parameter.

[0070] The deviation of the preset operating parameters of each component in the target equipment is determined according to the following formula:

[0071]

[0072] Where σ represents the deviation of the preset operating parameters.

[0073] In one exemplary embodiment provided in this disclosure, the deviation of the target device's preset operating parameters is determined by combining the initial operating state evaluation scores of each component, including:

[0074] When the initial operating status evaluation score of any component is within the preset range, the deviation of the preset operating parameters of the target device is determined as the preset condition.

[0075] Specifically, the current deviation of each component is calculated using the following formula:

[0076] Δ=|x0-μ|

[0077] Where Δ represents the current deviation, and x0 represents the current preset operating parameter data for each component;

[0078] If Δ≤6σ, the initial operating status assessment score of the corresponding component is determined to be 95 points, and the deviation of the preset operating parameters of the corresponding component is determined to be of the excellent level. If 6σ<Δ≤12σ, the initial operating status assessment score of the corresponding component is determined to be 85 points, and the deviation of the preset operating parameters of the corresponding component is determined to be of the normal level. If Δ>12σ, and all preset operating parameter data do not exceed the level 2 alarm range in the standard operating procedure, the deviation of the preset operating parameters of the corresponding component is determined to be of the deterioration level, and the initial operating status assessment score of the corresponding component is determined to be 70 points. If at least one preset operating parameter data exceeds the level 2 alarm range in the standard operating procedure, but does not exceed the level 1 alarm range in the standard or operating procedure, the deviation of the preset operating parameters of the corresponding component is determined to be of the abnormal level, and the initial operating status assessment score of the corresponding component is determined to be 60 points. If at least one preset operating parameter data exceeds the level 1 alarm range in the standard or operating procedure, the deviation of the preset operating parameters of the corresponding component is determined to be of the severe level, and the initial operating status assessment score of the corresponding component is determined to be 50 points.

[0079] In this embodiment, to ensure the accuracy and effectiveness of equipment evaluation, a two-level weighting system (component-to-whole) and the "weakest link" principle are used to quantitatively evaluate the overall equipment status. The specific steps are as follows:

[0080] After determining the initial operating status evaluation scores of each component of the target device, if at least one initial operating status evaluation score falls into a preset range, which in this embodiment is set to the corresponding abnormal and severe score range, i.e. below 65 points, then the deviation of the preset operating parameters of the target device is directly considered to be abnormal or severe based on the score range that the component falls into.

[0081] If the initial operating status evaluation scores of all components are outside the preset range, the deviation of the target device's preset operating parameters is determined based on the weighted algorithm and the initial operating status evaluation scores of all components.

[0082] α*a+β*b+γ*c+...=Core1

[0083] In the formula, α, β, γ... represent the weights corresponding to different components, which can be determined according to the importance of the corresponding components, satisfying ∑α+β+γ+...=1. a, b, c... represent multiple components of the target device. Core1 represents the deviation of the target device's preset operating parameters, which can also be represented as the operating status score of the target device.

[0084] In one exemplary embodiment provided in this disclosure, determining the vibration changes of the target device based on vibration data within a preset time period specifically includes:

[0085] Based on vibration data within a preset time period, the initial vibration change of the target equipment is determined, and the deviation ratio between the initial vibration change and a preset threshold is determined. The vibration data used is determined by the peak-to-peak value (displacement) or single-peak value (velocity and acceleration) of the target equipment, along with characteristic values ​​obtained through signal processing. This embodiment refers to... Figure 2 As shown, vibration acceleration is represented by a single peak value. When assessing vibration changes, the relative change value and the absolute change value of vibration acceleration are assessed separately. The relative change value refers to the difference between the data of vibration acceleration at the previous moment and the data at the next moment, and the ratio of the relative change value to the data at the next moment. The absolute change value is the difference between the data of vibration acceleration at the previous moment and the data at the next moment.

[0086] Based on the deviation ratio, the vibration variation of the target equipment is determined, specifically as follows:

[0087] A preset threshold is obtained based on the overall condition level, which is the alarm value specified by the reference standard. The preset threshold is related to the vibration data reference. Figure 2 As shown, the upper broken line represents the preset threshold, and the lower lines represent vibration data. The absolute or relative change value of the vibration data is compared with the threshold to obtain a score.

[0088] In this embodiment, the specific scoring principles for absolute and relative change values ​​are as follows: When the absolute change value of vibration is stable and less than 50% of the alarm value specified by the reference standard, the corresponding vibration state change is rated as excellent, and a vibration change score of 95 points is awarded; when the absolute change value of vibration is less than 80% of the yellow alarm value specified by the preset threshold and greater than 50% of the yellow alarm value specified by the preset threshold, the corresponding vibration state change is rated as normal, and a vibration change score of 85 points is awarded; when the absolute change value is less than the yellow alarm value and greater than 80% of the yellow alarm value specified by the preset threshold, the corresponding vibration state change is rated as... For a deterioration level, a vibration change score of 70 points is awarded; when the vibration change is greater than the yellow alarm value but less than the red alarm value, the corresponding vibration state change is classified as abnormal, and a vibration change score of 60 points is awarded; when the vibration change is greater than the red alarm value, the corresponding vibration state change is classified as severe, and a vibration change score of 50 points is awarded; when the relative change value of vibration data measured between two consecutive measurements (with a time interval not exceeding 1 day) reaches 25% of the yellow alarm value specified by the preset threshold, if the absolute change value is less than the yellow alarm value, the corresponding deterioration level is awarded, and a score of 75 points is awarded; if the absolute change value is greater than the yellow alarm value, the corresponding severe level is awarded, and a score of 50 points is awarded.

[0089] In one exemplary embodiment provided in this disclosure, the specific steps for determining the above-mentioned energy efficiency compliance status include:

[0090] The current energy efficiency of the equipment is calculated based on real-time data measured by the SIS system of a thermal power plant, yielding secondary calculation parameters characterizing the equipment's performance, such as efficiency, terminal differential, and output. In this embodiment, the evaluation steps for the energy efficiency compliance of the target equipment are as follows:

[0091] The calculated current energy efficiency index is compared with the equipment design energy efficiency index to obtain a score.

[0092] In this embodiment, the specific scoring principle is as follows: the score is compared based on the percentage of the calculated current energy efficiency that meets the equipment's energy efficiency index: if it reaches 98% of the design value, the corresponding energy efficiency compliance is excellent, and the energy efficiency status score is 95 points; if it reaches 90% of the design value, the corresponding energy efficiency compliance is normal, and the score is 90 points; if it reaches 80% of the design value, the corresponding energy efficiency compliance is deteriorated, and the energy efficiency status score is 70 points; if it is below 75% of the design value, the corresponding energy efficiency compliance is abnormal, and the energy efficiency status score is 60 points.

[0093] In one exemplary embodiment provided in this disclosure, determining the aforementioned pre-defined structural anomaly includes:

[0094] The inspection covers four aspects: whether the target equipment's pre-installed structure has any leaks, abnormal noises, abnormal odors, and whether the target equipment's accessory structure is complete.

[0095] If none of the above situations occur, the corresponding preset structural anomaly is rated as excellent, and the structural status score is 100 points. If only one of the above situations occurs, and there is no harm to personal or equipment safety, the corresponding preset structural anomaly is rated as normal, and the structural status score is 80 points. If two or more situations occur, and there is no harm to personal or equipment safety, the corresponding preset structural anomaly is rated as deteriorated, and the structural status score is 70 points. If there is a harm to equipment or personal safety, if it has a certain impact on equipment or personal safety, the corresponding preset structural anomaly is rated as deteriorated, and the structural status score is 70 points. If it seriously affects equipment or personal safety, the corresponding preset structural anomaly is rated as abnormal, and the structural status score is 60 points. If it directly endangers equipment or personal safety, the corresponding preset structural anomaly is rated as severe, and the structural status score is 50 points.

[0096] In one exemplary embodiment provided in this disclosure, determining the aforementioned lifetime usage includes:

[0097] First, identify the main or critical components in the target equipment and calculate their service life. Compile the service lives of these critical components and select the component with the shortest service life as the evaluation value for the overall equipment lifespan.

[0098] The service life is compared with the design life to obtain a score. In this embodiment, the specific scoring principles are as follows: if the service life does not exceed 80% of the design life, the corresponding service life is considered excellent, and a service life score of 100 points is awarded; if the service life does not exceed 90% of the design life, the corresponding service life is considered normal, and a service life score of 85 points is awarded; if the service life does not exceed 98% of the design life, the corresponding service life is considered deteriorated, and a service life score of 75 points is awarded. If the service life exceeds 100% of the design life, and other assessments indicate that the equipment is still in normal condition, then the service life of the equipment is extended according to the actual situation.

[0099] In one exemplary embodiment provided in this disclosure, the overall state of the target equipment is determined by combining factors such as deviations from preset operating parameters, energy efficiency compliance, vibration changes, preset structural anomalies, and lifespan usage, including:

[0100] Based on the deviation of preset operating parameters, energy efficiency compliance, vibration changes, preset structural anomalies, and lifespan, the operating status score, energy efficiency status score, vibration status score, structural status score, and lifespan status score of the target equipment are determined respectively.

[0101] If at least one score among the operational status score, energy efficiency score, vibration status score, structural status score, and lifespan status score falls within a preset range, the overall status of the target equipment is determined to be the preset status, i.e.:

[0102] If any of the five status scores calculated above is below 65, and the corresponding status is abnormal or severe, then the overall status of the target device is determined to be abnormal or severe.

[0103] If the scores for operational status, energy efficiency, vibration, structural condition, and lifespan are all outside the preset range (i.e., all five calculated scores are above 65), then a weighted algorithm can be used to determine the overall status level and score of the target equipment based on these scores. This allows staff to assess the target equipment as a whole and, based on the overall status level and score, make targeted maintenance recommendations such as "immediate shutdown for maintenance," "strengthen monitoring," or "periodic inspection."

[0104] In summary, the above method breaks through the limitations of traditional equipment evaluation methods that rely on a single indicator. It integrates data from five key dimensions: the impact of operating parameter data on process status, the economic impact of current energy efficiency, the mechanical health impact of vibration changes, the potential risk impact of structural anomalies, and the impact of equipment aging on equipment lifespan.

[0105] By utilizing data from five key dimensions, cross-validation can be achieved, significantly reducing the likelihood of false alarms and missed alarms. Furthermore, by calculating the overall comprehensive status of the target equipment based on a weighted average across these five key dimensions, an unprecedentedly comprehensive, accurate, and quantitative assessment of the health status of critical equipment in thermal power plants is realized. This provides highly practical and directly applicable insights for equipment management and operational optimization, thereby effectively improving the economy, reliability, and safety of power plant operations.

[0106] This disclosure also provides a comprehensive condition assessment system for thermal power plant equipment, which can be found here. Figure 3 As shown, it includes:

[0107] The data acquisition module acquires the preset operating parameter data, current energy efficiency and design energy efficiency indicators of the current target equipment, as well as vibration data within a preset time period, and determines the preset structural anomalies and the lifespan of preset components of the target equipment.

[0108] The operating parameter deviation calculation module determines the deviation of the target device's preset operating parameters based on the target device's preset operating parameter data and preset optimal operating parameters;

[0109] The energy efficiency compliance calculation module determines the energy efficiency compliance status of the target equipment based on the current energy efficiency and design energy efficiency indicators.

[0110] The vibration change calculation module determines the vibration change of the target equipment based on vibration data within a preset time period.

[0111] The comprehensive status confirmation module determines the comprehensive status of the target equipment by combining the deviation of the target equipment's preset operating parameters, the compliance of energy efficiency, the changes in vibration, the preset structural anomalies, and the service life.

[0112] Furthermore, the operating parameter deviation calculation module specifically includes:

[0113] The deviation of the preset operating parameters of the target device is determined according to the following formula:

[0114]

[0115] Where σ represents the deviation of the preset operating parameters, n represents the type of preset operating parameters of the target device, and x iThis represents the preset operating parameter data, where μ represents the preset optimal operating parameters.

[0116] Furthermore, the operating parameter deviation calculation module specifically includes:

[0117] The target device includes multiple components. For each component, based on the current preset operating parameter data of the component and the preset optimal operating parameters of the component, the deviation of the preset operating parameters of the component is determined, and the initial operating state evaluation score of the component is determined according to the deviation of the preset operating parameters of the component.

[0118] By combining the initial operating status evaluation scores of each component, the deviation of the preset operating parameters of the target device is determined.

[0119] Furthermore, the operating parameter deviation calculation module specifically includes:

[0120] When the initial operating status evaluation score of any of the components is within a preset range, the deviation of the preset operating parameters of the target device is determined to be a preset condition.

[0121] When the initial operating status evaluation scores of all the components are outside the preset range, the deviation of the preset operating parameters of the target device is determined based on the weighted algorithm and the initial operating status evaluation scores of all the components.

[0122] Furthermore, the vibration change calculation module specifically includes:

[0123] Based on the vibration data within a preset time period, determine the initial vibration change of the target device, and determine the deviation ratio between the initial vibration change and a preset threshold.

[0124] The vibration variation of the target equipment is determined based on the deviation ratio.

[0125] Furthermore, the comprehensive status confirmation module specifically includes:

[0126] Based on the deviation of the preset operating parameters, the energy efficiency compliance, the vibration change, the preset structural anomaly, and the lifespan, the operating status score, energy efficiency status score, vibration status score, structural status score, and lifespan status score of the target equipment are determined respectively.

[0127] If at least one of the operating status score, energy efficiency score, vibration status score, structural status score, and lifespan status score falls within a preset range, the overall status of the target equipment is determined to be the preset status.

[0128] Furthermore, the comprehensive status confirmation module also includes:

[0129] If the operating status score, energy efficiency score, vibration status score, structural status score, and lifespan status score are all outside the preset range, the overall status of the target equipment is determined based on a weighted algorithm, combining the operating status score, energy efficiency score, vibration status score, structural status score, and lifespan status score.

[0130] This disclosure also provides a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to perform the comprehensive condition assessment method for thermal power plant equipment as described above.

[0131] This disclosure also provides an electronic device, including a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, it implements the comprehensive condition assessment method for thermal power plant equipment as described above.

[0132] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement embodiments of the present disclosure 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 (such as 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 present disclosure described and / or claimed herein.

[0133] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0134] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0135] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a comprehensive condition assessment method for thermal power plant equipment.

[0136] In some embodiments, a comprehensive condition assessment method for thermal power plant equipment may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the comprehensive condition assessment method for thermal power plant equipment described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform a comprehensive condition assessment method for thermal power plant equipment by any other suitable means (e.g., by means of firmware).

[0137] 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 (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), 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.

[0138] Computer programs used to implement the methods of this disclosure 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 apparatus, 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.

[0139] In the context of this disclosure, 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 can be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can 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 (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0140] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device for displaying information to the user, such as a CRT (cathode ray tube) or an LCD (liquid crystal display); 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).

[0141] 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 (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0142] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through 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 hosting product within the cloud computing service system. It addresses the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0143] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0144] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0145] Although embodiments of the present disclosure have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present disclosure.

Claims

1. A comprehensive condition assessment method for thermal power plant equipment, characterized in that, include: Acquire the preset operating parameter data, current energy efficiency and design energy efficiency indicators of the current target equipment, as well as vibration data within a preset time period, and determine the preset structural abnormalities and lifespan of the preset components of the target equipment; Based on the preset operating parameter data and preset optimal operating parameters of the target device, determine the deviation of the preset operating parameters of the target device; Based on the current energy efficiency and design energy efficiency indicators, determine the energy efficiency compliance status of the target equipment; Based on the vibration data within a preset time period, the vibration changes of the target equipment are determined; The overall status of the target equipment is determined by combining the deviation of the preset operating parameters, the energy efficiency compliance, the vibration changes, the preset structural anomalies, and the service life.

2. The comprehensive condition assessment method for thermal power plant equipment according to claim 1, characterized in that, The step of determining the deviation of the target device's preset operating parameters based on the preset operating parameter data and preset optimal operating parameters includes: The deviation of the preset operating parameters of the target device is determined according to the following formula: Where σ represents the deviation of the preset operating parameters, n represents the type of preset operating parameters of the target device, and x i This represents the preset operating parameter data, where μ represents the preset optimal operating parameters.

3. The comprehensive condition assessment method for thermal power plant equipment according to claim 2, characterized in that, The step of determining the deviation of the target device's preset operating parameters based on the preset operating parameter data and preset optimal operating parameters includes: The target device includes multiple components. For each component, based on the current preset operating parameter data of the component and the preset optimal operating parameters of the component, the deviation of the preset operating parameters of the component is determined, and the initial operating state evaluation score of the component is determined according to the deviation of the preset operating parameters of the component. By combining the initial operating status evaluation scores of each component, the deviation of the preset operating parameters of the target device is determined.

4. The comprehensive condition assessment method for thermal power plant equipment according to claim 3, characterized in that, The step of determining the deviation of the target device's preset operating parameters by combining the initial operating status evaluation scores of each component includes: When the initial operating status evaluation score of any of the components is within a preset range, the deviation of the preset operating parameters of the target device is determined to be a preset condition. When the initial operating status evaluation scores of all the components are outside the preset range, the deviation of the preset operating parameters of the target device is determined based on the weighted algorithm and the initial operating status evaluation scores of all the components.

5. The comprehensive condition assessment method for thermal power plant equipment according to claim 1, characterized in that, Determining the vibration changes of the target equipment based on the vibration data within a preset time period includes: Based on the vibration data within a preset time period, determine the initial vibration change of the target device, and determine the deviation ratio between the initial vibration change and a preset threshold. The vibration variation of the target equipment is determined based on the deviation ratio.

6. The comprehensive condition assessment method for thermal power plant equipment according to claim 1, characterized in that, The comprehensive status of the target equipment is determined by combining the deviation of the preset operating parameters, the energy efficiency compliance, the vibration changes, the preset structural anomalies, and the service life, including: Based on the deviation of the preset operating parameters, the energy efficiency compliance, the vibration change, the preset structural anomaly, and the lifespan, the operating status score, energy efficiency status score, vibration status score, structural status score, and lifespan status score of the target equipment are determined respectively. If at least one of the operating status score, energy efficiency score, vibration status score, structural status score, and lifespan status score falls within a preset range, the overall status of the target equipment is determined to be the preset status.

7. The comprehensive condition assessment method for thermal power plant equipment according to claim 6, characterized in that, The method further includes: If the operating status score, energy efficiency score, vibration status score, structural status score, and lifespan status score are all outside the preset range, the overall status of the target equipment is determined based on a weighted algorithm, combining the operating status score, energy efficiency score, vibration status score, structural status score, and lifespan status score.

8. A comprehensive condition assessment system for thermal power plant equipment, characterized in that, include: The data acquisition module acquires the preset operating parameter data, current energy efficiency and design energy efficiency indicators of the current target equipment, as well as vibration data within a preset time period, and determines the preset structural abnormalities and lifespan of the preset components of the target equipment. The operating parameter deviation calculation module determines the deviation of the target device's preset operating parameters based on the preset operating parameter data and the preset optimal operating parameters. The energy efficiency compliance calculation module determines the energy efficiency compliance status of the target equipment based on the current energy efficiency and the design energy efficiency index. The vibration change calculation module determines the vibration change of the target equipment based on the vibration data within a preset time period. The comprehensive status confirmation module determines the comprehensive status of the target equipment by combining the deviation of the preset operating parameters, the energy efficiency compliance, the vibration changes, the preset structural anomalies, and the lifespan of the target equipment.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a terminal device, cause the terminal device to perform a comprehensive condition assessment method for thermal power plant equipment as described in any one of claims 1 to 7.

10. An electronic device comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements a comprehensive condition assessment method for thermal power plant equipment as described in any one of claims 1 to 7.

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