Power equipment asset management method, system and device and storage medium

Abstract

The invention relates to the technical field of power equipment management, and discloses a power equipment asset management method, system and device and a storage medium, the power equipment asset management system comprises a data collection unit, a data processing unit, a comprehensive analysis unit, an evaluation management unit and a result display unit, the data processing unit performs feature analysis to obtain a feature evaluation value; the state change analysis calculates an operation parameter fluctuation coefficient and a change rate to obtain a state change evaluation value; load fluctuation analysis obtains a load fluctuation evaluation value based on a load value in an acquisition period; performing equipment aging analysis to obtain an aging evaluation value by considering the fault frequency, the operation duration and the fault time interval; the comprehensive analysis unit obtains a comprehensive score coefficient according to the feature evaluation value; the evaluation management unit generates different risk signals according to comparison between the coefficient and a preset threshold value; the result display unit displays the risk signal to operation and maintenance personnel so as to take management measures; according to the invention, data is comprehensively collected, scientific evaluation is realized, and efficient decision support is provided for equipment management.

Description

Technical Field

[0001] The present invention relates to the technical field of power equipment management, and in particular to a power equipment asset management method, system, device and storage medium. Background Art

[0002] With the continuous development and expansion of the power system, the number and types of power equipment are also increasing. As the core component of the power system, the safe and stable operation of power equipment is crucial to ensure the reliability of power supply. However, since power equipment operates under high load and complex environment for a long time, it is prone to various faults and problems, which brings great challenges to the safe and stable operation of the power system.

[0003] On the one hand, traditional asset management methods often rely on manual records and empirical judgments, lack comprehensive collection and in-depth analysis of equipment data, and are difficult to accurately assess the actual operating status and potential risks of equipment. On the other hand, there is a lack of systematic analysis methods for equipment status changes, load fluctuations, and aging conditions, and it is impossible to promptly discover possible problems with equipment, resulting in an increased probability of equipment failures and affecting the stable operation of the power system. At the same time, there are also deficiencies in risk determination and signal generation, making it difficult to provide accurate and effective management basis for operation and maintenance personnel, making operation and maintenance personnel lack pertinence and timeliness in managing power equipment, reducing the efficiency and quality of power equipment asset management.

[0004] In summary, in order to solve the problems existing in the existing power equipment asset management and improve the management level and operation reliability of power equipment, a new power equipment asset management method, system, device and storage medium are urgently needed. Summary of the invention

[0005] The purpose of the present invention is to provide a method, system, device and storage medium for power equipment asset management, which solves the technical problems raised in the background technology.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A method, system, device and storage medium for power equipment asset management, comprising:

[0008] A data collection unit, used to collect equipment data of target power equipment, the equipment data including equipment operation information, power load information and historical fault information;

[0009] A data processing unit, used to perform feature analysis on the target power equipment according to the equipment data of the target power equipment and obtain a corresponding feature evaluation value;

[0010] A comprehensive analysis unit, used to perform a comprehensive score analysis on the target power equipment according to the state change evaluation value P1, the load fluctuation evaluation value P2, and the aging evaluation value P3 of the target power equipment, and obtain a comprehensive score coefficient of the target power equipment;

[0011] An assessment management unit, used to determine and generate different risk signals based on the comprehensive score coefficient of the target power equipment;

[0012] The result display unit is used to display different risk signals to relevant operation and maintenance personnel, and the relevant operation and maintenance personnel take different management measures to manage the target power equipment according to the corresponding risk signals.

[0013] As a further embodiment of the present invention:

[0014] The equipment operation information is the operation parameters of various attributes obtained by real-time monitoring of the target power equipment through preset sensors, including but not limited to voltage, current, and power;

[0015] The power load information is obtained from the corresponding monitoring equipment set up in the power system, which includes the load value at each collection time;

[0016] The historical fault data is obtained from the maintenance records of the target power equipment, which includes but is not limited to the number of faults of the target power, the time of each fault, and the total operating time of the target power equipment.

[0017] As a further solution of the present invention: wherein the characteristic analysis includes: state change analysis, load fluctuation analysis and equipment aging analysis;

[0018] Feature evaluation values ​​include:

[0019] A state change evaluation value obtained by state change analysis;

[0020] Load fluctuation evaluation value obtained by load fluctuation analysis;

[0021] Aging assessment value obtained from equipment aging analysis.

[0022] As a further solution of the present invention: the state change analysis method is as follows:

[0023] StepA1. Select an operating parameter corresponding to an attribute;

[0024] In multiple continuous collection cycles, extract the operating parameters of the attribute corresponding to n collection time nodes and mark them as D according to the time trend. i，j , i = 1, 2, ... n, j = 1, 2, ... m, m represents the number of multiple acquisition cycles;

[0025] Step A2: Collect the rated parameters of the target power equipment at the same time, including but not limited to rated voltage, rated current, and rated power, and then mark them as DE j ;

[0026] Among them, the rated parameters are extracted from the nameplate of the target power equipment;

[0027] Step A3, through Calculate the fluctuation coefficient K of the attribute in each collection cycle j ;

[0028] StepA4, through Calculate the change rate K0 between each fluctuation coefficient of the attribute in all adjacent acquisition cycles;

[0029] Among them, K j and K j+1 The relationship between refers to the individual fluctuation coefficients in adjacent acquisition cycles;

[0030] StepA5: Calculate the change rate of each fluctuation coefficient of each attribute in all adjacent acquisition cycles according to the method of StepA1 to StepA4, and record it as K0 t , t = 1, 2, ... e, e represents the number of various attributes in the device data;

[0031] StepA6. Pass Calculate the state change evaluation value P1 of the target power equipment;

[0032] In the formula, α t , β1 and β2 are the corresponding preset weight factors, K0 e It is represented as the last collection period among multiple consecutive collection periods according to the time trend, and the time interval between the last collection period and the current time node is the smallest.

[0033] As a further solution of the present invention: the load fluctuation analysis method is as follows:

[0034] Step B1, selecting a collection cycle from multiple consecutive collection cycles;

[0035] Extract the load values ​​at n acquisition moments and mark them as F according to the time trend i , i=1, 2, ... n;

[0036] Step B2, obtain the load values ​​at n acquisition moments and mark them as FP;

[0037] Step B3, through Calculate the load fluctuation assessment value P2 corresponding to the n collection moments in the collection cycle.

[0038] As a further embodiment of the present invention:

[0039] The equipment aging analysis method is as follows:

[0040] Step C1, obtain the number of faults of the target power equipment and mark it as r;

[0041] At the same time, the total operating time of the equipment is marked as Y;

[0042] Step C1, obtaining the corresponding fault occurrence time of each fault of the target power equipment;

[0043] Then, according to the time when the fault occurs and the trend of time, the fault time intervals between two adjacent faults are obtained and marked as Sg, where g=1, 2, ... r-1;

[0044] Step C3, through The corresponding aging assessment value P3 of the target electric equipment is calculated.

[0045] As a further embodiment of the present invention:

[0046] The comprehensive score analysis method is to obtain the comprehensive score coefficient Z of the target power equipment through: Z=λ1×P1+λ2×P2+λ2×P3.

[0047] As a further solution of the present invention: the determination method of the evaluation management unit is as follows:

[0048] Compare the comprehensive score coefficient Z of the target power equipment with the preset score determination thresholds My1, My2 and My3: wherein My1<My2<My3;

[0049] If Z<My1, a low-risk signal is generated for the target power equipment, which indicates that the equipment is in good condition;

[0050] If My1≤Z<My2, a medium risk signal is generated for the target power equipment, and the medium risk signal indicates that the equipment status is general;

[0051] If Z≥My3, a high-risk signal is generated for the target power equipment, and the high-risk signal indicates that the state of the target power equipment is poor.

[0052] A method for managing power equipment assets, which is implemented by a power equipment asset management system, and includes the following steps:

[0053] Step 1: Information Collection

[0054] Collect equipment data of target power equipment, including equipment operation information, power load information and historical fault information;

[0055] Step 2: Information Processing

[0056] Performing feature analysis on the target power equipment according to the equipment data of the target power equipment, and obtaining a corresponding feature evaluation value;

[0057] Step 3: Comprehensive Analysis

[0058] According to the state change evaluation value P1, load fluctuation evaluation value P2, and aging evaluation value P3 of the target power equipment, a comprehensive score analysis is performed on the target power equipment, and a comprehensive score coefficient of the target power equipment is obtained;

[0059] Step 4: Evaluate Management Unit

[0060] Determine and generate different risk signals based on the comprehensive score coefficient of the target power equipment;

[0061] Step 5: Results display

[0062] Different risk signals are displayed to relevant operation and maintenance personnel, who take different management measures to manage the target power equipment based on the corresponding risk signals.

[0063] An electric power equipment asset management device, the device comprising a sensor module, a central processor and a display, the device is used in the electric power equipment asset management system;

[0064] The sensor module is used to realize the function of the data collection unit;

[0065] The central processing unit is used to realize the functions of the data processing unit, the comprehensive analysis unit, and the evaluation management unit;

[0066] The display is used to realize the function of the result display unit.

[0067] A storage medium of an electric power equipment asset management system, the storage medium is used to store all programs of the electric power equipment asset management system, and all programs are used to execute an electric power equipment asset management system.

[0068] Beneficial effects of the present invention:

[0069] The present invention collects equipment operation information, power load information and historical fault information through a data collection unit, covering key data of various aspects of the target power equipment, and providing a comprehensive data basis for accurately evaluating the equipment status; feature analysis includes state change analysis, load fluctuation analysis and equipment aging analysis, which deeply analyzes equipment characteristics from different angles, and can more comprehensively understand the operating status and potential risks of the equipment.

[0070] In the present invention, the state change analysis can accurately reflect the state change of the equipment at different time nodes by calculating the fluctuation coefficient and the change rate of the equipment operation parameters, and provides a scientific basis for timely discovering equipment abnormalities; the load fluctuation analysis is based on the load value within the acquisition period, and calculates the load fluctuation evaluation value, which is helpful to evaluate the stability and reliability of the equipment under load changes; the equipment aging analysis comprehensively considers factors such as the number of faults, the total operating time and the fault time interval, and can objectively evaluate the aging degree of the equipment, providing a reference for equipment maintenance and updating.

[0071] In the present invention, the comprehensive analysis unit performs a comprehensive score analysis on the state change assessment value, the load fluctuation assessment value and the aging assessment value to obtain a comprehensive score coefficient of the target power equipment, which can comprehensively reflect the overall state of the equipment; the assessment management unit generates different risk signals based on the comparison between the comprehensive score coefficient and the preset score judgment threshold, so that the operation and maintenance personnel can quickly and accurately understand the risk level of the equipment and take corresponding management measures.

[0072] In the present invention, the result display unit displays the risk signal to the relevant operation and maintenance personnel, and provides them with intuitive equipment status information, so that the operation and maintenance personnel can take different management measures to manage the target power equipment in time, thereby improving the efficiency and pertinence of equipment management.

[0073] This invention provides a scientific and efficient method and system for power equipment asset management, which helps to improve the reliability and stability of power equipment, reduce equipment failure rate, and ensure the safe operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] The present invention will be further described below in conjunction with the accompanying drawings.

[0075] Figure 1 The present invention is a system block diagram of an electric power equipment asset management method, system, device and storage medium. DETAILED DESCRIPTION

[0076] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0077] Embodiment 1

[0078] See also Figure 1 As shown, the present invention is a power equipment asset management system, comprising:

[0079] A data collection unit, used to collect equipment data of target power equipment, the equipment data including equipment operation information;

[0080] In this embodiment, the equipment operation information is the operation parameters of various attributes obtained by real-time monitoring of the target power equipment through preset sensors, including but not limited to voltage, current, and power;

[0081] A data processing unit, used to analyze the state change of the target power equipment according to the operating parameters of multiple attributes in the equipment data in multiple continuous collection cycles;

[0082] The state change analysis method is as follows:

[0083] StepA1. Select an operating parameter corresponding to an attribute;

[0084] In multiple continuous collection cycles, extract the operating parameters of the attribute corresponding to n collection time nodes and mark them as D according to the time trend. i，j , i = 1, 2, ... n, j = 1, 2, ... m, m represents the number of multiple acquisition cycles;

[0085] Step A2: Collect the rated parameters of the target power equipment at the same time, including but not limited to rated voltage, rated current, and rated power, and then mark them as DE j ;

[0086] Among them, the rated parameters are extracted from the nameplate of the target power equipment;

[0087] Step A3, through Calculate the fluctuation coefficient K of the attribute in each collection cycle j ;

[0088] StepA4, through Calculate the change rate K0 between each fluctuation coefficient of the attribute in all adjacent acquisition cycles;

[0089] Among them, K j and K j+1 The relationship between refers to the individual fluctuation coefficients in adjacent acquisition cycles;

[0090] StepA5: Calculate the change rate of each fluctuation coefficient of each attribute in all adjacent acquisition cycles according to the method of StepA1 to StepA4, and record it as K0 t , t = 1, 2, ... e, e represents the number of various attributes in the device data;

[0091] StepA6. Pass Calculate the state change evaluation value P1 of the target power equipment;

[0092] In the formula, α t , β1 and β2 are the corresponding preset weight factors, K0 e It is represented as the last collection period among multiple consecutive collection periods according to the time trend, and its time interval with the current time node is the smallest;

[0093] The evaluation management unit is used to compare the state change evaluation value P1 of the target power equipment with the preset state change determination thresholds Uy1, Uy2 and Uy3:

[0094] Among them, Uy1<Uy2<Uy3;

[0095] If P1<Uy1, a first-level operation risk signal is generated for the target power equipment;

[0096] If Uy1≤P1<Uy2, a secondary operation risk signal is generated for the target power equipment;

[0097] If P1≥Uy3, a level 3 operation risk signal is generated for the target power equipment;

[0098] in,

[0099] The first-level operational risk signal indicates that the status changes of the target power equipment need to be closely monitored to ensure that any minor abnormal trends can be discovered in time;

[0100] The second-level signal of operation risk indicates that it is necessary to increase the inspection intensity of the target power equipment and shorten the inspection cycle so as to timely discover and deal with potential problems. Professional technicians should be organized to conduct detailed diagnosis and analysis of the equipment to determine the causes of state changes and potential risk points.

[0101] The third-level operation risk signal indicates an emergency situation and the target power equipment must be stopped immediately for comprehensive inspection and maintenance. At the same time, backup equipment must be started quickly to ensure the continuity of power supply and repair the faulty equipment.

[0102] The result display unit is used to display different risk signals to relevant operation and maintenance personnel, and the relevant operation and maintenance personnel take different management measures to manage the target power equipment according to the corresponding risk signals.

[0103] This embodiment can accurately evaluate the operating status of the equipment by collecting equipment data of the target power equipment and analyzing the state changes of the equipment. The fluctuation coefficient and change rate are calculated using the operating parameters of multiple attributes to obtain the state change evaluation value, and then generate different levels of operation risk signals, so that relevant operation and maintenance personnel can take targeted management measures according to the risk signals, effectively improve the reliability and stability of the equipment, and ensure the safety and continuity of power supply.

[0104] Embodiment 2

[0105] As the second embodiment of the present invention, when the present application is implemented, compared with the first embodiment, the technical solution of the present embodiment is different from that of the first embodiment only in that,

[0106] Equipment data also includes power load information;

[0107] In this embodiment, the power load information is obtained from a corresponding monitoring device arranged in the power system, which includes the load value at each acquisition time;

[0108] The data processing unit is also used to obtain the load values ​​at n collection moments in the last collection cycle of multiple consecutive collection cycles, and perform load fluctuation analysis on the target power equipment according to the load values ​​in the equipment data;

[0109] The load fluctuation analysis method is as follows:

[0110] Step B1, selecting a collection cycle from multiple consecutive collection cycles;

[0111] Extract the load values ​​at n acquisition moments and mark them as F according to the time trend i , i=1, 2, ... n;

[0112] Step B2, obtain the load values ​​at n acquisition moments and mark them as FP;

[0113] Step B3, through Calculate the load fluctuation assessment value P2 corresponding to n collection moments in the collection cycle;

[0114] The evaluation management unit is further used to compare the load fluctuation evaluation value P2 of the target power equipment with the preset load fluctuation determination thresholds Fy1, Fy2 and Fy3:

[0115] Among them, Fy1<Fy2<Fy3;

[0116] If P2<Fy1, a load risk level 1 signal is generated for the target power equipment;

[0117] If Fy1≤P2<Fy2, a load risk level 2 signal is generated for the target power equipment;

[0118] If P2≥Fy3, a load risk level 3 signal is generated for the target power equipment.

[0119] in,

[0120] The first level load risk signal indicates that the load risk is relatively low at this time. Real-time monitoring of the load fluctuation of the target power equipment is maintained to detect any potential change trend in time.

[0121] The second-level load risk signal indicates that the load risk is medium at this stage. Adjust the operation mode of the equipment, such as adopting rotation operation, switching of backup equipment, etc., to reduce the load pressure of a single device, or locally upgrade or transform the equipment to improve the capacity and performance of the equipment to better cope with load fluctuations; increase the frequency of equipment inspections to promptly discover and deal with potential equipment failures and hidden dangers.

[0122] The load risk level 3 signal indicates that this is a high-risk state and emergency measures must be taken immediately, such as immediately forcibly interrupting some interruptible loads to reduce the overall load of the power grid, organizing professional and technical personnel to conduct emergency inspection and maintenance of equipment, troubleshooting, and restoring normal operation of the equipment.

[0123] This embodiment adds consideration to power load information on the basis of the first embodiment. By acquiring power load information and performing load fluctuation analysis, the load conditions of the target power equipment at different acquisition times can be timely understood. Generating load risk signals of different levels helps operation and maintenance personnel to take corresponding measures to adjust the equipment operation mode, perform local upgrades or modifications, etc., reduce the load pressure of the equipment, improve the equipment's ability to cope with load fluctuations, and further ensure the stable operation of the power system.

[0124] Embodiment 3

[0125] As the third embodiment of the present invention, when the present application is implemented, compared with the first and second embodiments, the technical solution of this embodiment is to combine the solutions of the first and second embodiments, and the difference between the technical solution of this embodiment and the first and second embodiments is only in this embodiment;

[0126] Equipment data also includes historical fault information;

[0127] In this embodiment, the historical fault data is obtained from the maintenance records of the target power equipment, which includes but is not limited to the number of faults of the target power, the time of each fault, and the total operation time of the target power equipment;

[0128] The data processing unit is also used to perform equipment aging analysis on the target power equipment based on the maintenance records in the equipment data;

[0129] The specific method is as follows:

[0130] Step C1, obtain the number of faults of the target power equipment and mark it as r;

[0131] At the same time, the total operating time of the equipment is marked as Y;

[0132] Step C1, obtaining the corresponding fault occurrence time of each fault of the target power equipment;

[0133] Then, according to the time when the fault occurs and the trend of time, the fault time intervals between two adjacent faults are obtained and marked as Sg, where g=1, 2, ... r-1;

[0134] Step C3, through Calculate the corresponding aging assessment value P3 of the target power equipment;

[0135] The evaluation management unit is also used to compare the aging evaluation value P3 of the target power equipment with the preset aging judgment thresholds Ly1, Ly2 and Ly3:

[0136] Among them, Ly1<Ly2<Ly3;

[0137] If P3<Ly1, a first-level aging risk signal is generated for the target power equipment;

[0138] If Ly1≤P3<Ly2, a secondary aging risk signal is generated for the target power equipment;

[0139] If P3≥Ly3, a level 3 aging risk signal is generated for the target power equipment.

[0140] in,

[0141] A level 1 aging risk signal indicates that the aging of the equipment needs to be closely monitored to ensure that any early signs of aging can be detected in a timely manner;

[0142] Aging risk level 2 signal indicates that the frequency and depth of equipment inspections need to be increased, with a focus on parts that are prone to aging problems, such as insulation parts and connectors. Parts that have already shown signs of aging can be partially repaired or replaced to prevent further expansion of aging problems.

[0143] The third level signal of chemical risk indicates that the equipment needs to be stopped immediately and a comprehensive aging assessment and safety risk assessment must be conducted to determine whether the equipment can continue to operate safely. If the equipment is seriously aged, a comprehensive overhaul or replacement of key components may be required, or even replacement of the entire equipment may be considered.

[0144] This embodiment introduces historical fault information to perform equipment aging analysis on the target power equipment. By obtaining data such as the number of faults, total operating time, and fault time interval, the aging assessment value is calculated to generate aging risk signals of different levels. This enables operation and maintenance personnel to timely grasp the aging status of the equipment, take measures such as close monitoring, increasing the frequency and depth of inspections, local repairs or replacement of parts, etc., to prevent the aging problem from expanding, ensure the safe operation of the equipment, and extend the service life of the equipment.

[0145] Embodiment 4

[0146] As the fourth embodiment of the present invention, when the present application is implemented, compared with the first embodiment, the second embodiment and the third embodiment, the difference between the present embodiment and the first embodiment, the second embodiment and the third embodiment is that the present embodiment further includes:

[0147] A comprehensive analysis unit is used to perform a comprehensive score analysis on the target power equipment according to the state change evaluation value P1, the load fluctuation evaluation value P2, and the aging evaluation value P3 of the target power equipment; the method is to obtain the comprehensive score coefficient Z of the target power equipment through: Z = λ1×P1+λ2×P2+λ2×P3;

[0148] The evaluation management unit is also used to compare the comprehensive score coefficient Z of the target power equipment with the preset score determination thresholds My1, My2 and My3:

[0149] Among them, My1<My2<My3;

[0150] If Z < My1, a low-risk signal is generated for the target power equipment. The low-risk signal indicates that the equipment is in good condition and the maintenance cycle can be appropriately extended to reduce maintenance costs.

[0151] If My1≤Z<My2, a medium risk signal is generated for the target power equipment, which indicates that the equipment is more likely to fail and requires enhanced monitoring and preventive measures;

[0152] If Z≥My3, a high-risk signal is generated for the target power equipment, which indicates that the target power equipment is in a poor state and needs to be maintained or replaced in time.

[0153] This embodiment sets up a comprehensive analysis unit, performs comprehensive score analysis based on the state change assessment value, load fluctuation assessment value and aging assessment value, and obtains a comprehensive score coefficient. By comparing the comprehensive score coefficient with the score judgment threshold, low, medium and high risk signals are generated, providing a comprehensive and integrated equipment status assessment for operation and maintenance personnel. Low risk signals can appropriately extend the maintenance cycle to reduce costs, medium risk signals remind to strengthen monitoring and preventive measures, and high risk signals prompt timely maintenance or replacement, thereby improving the scientificity and efficiency of equipment management.

[0154] Embodiment 5

[0155] As the fifth embodiment of the present invention, when the present application is specifically implemented, compared with the first, second, third and fourth embodiments, the technical solution of this embodiment is to combine and implement the solutions of the above-mentioned first, second, third and fourth embodiments.

[0156] This embodiment combines the solutions of Embodiments 1, 2, 3, and 4, comprehensively considers multiple factors such as the operation information, power load information, and historical fault information of the target power equipment, and performs state change analysis, load fluctuation analysis, aging analysis, and comprehensive score analysis. It provides operation and maintenance personnel with a more systematic and accurate equipment status assessment and risk signals, enabling them to take more scientific and effective management measures to maximize the safety and stable operation of the target power equipment and improve the overall reliability and economy of the power system.

[0157] The present invention also provides a method for managing power equipment assets, which is implemented by a power equipment asset management system. The method includes the following steps:

[0158] Step 1: Information Collection

[0159] Collect equipment data of target power equipment, including equipment operation information, power load information and historical fault information;

[0160] Step 2: Information Processing

[0161] Performing feature analysis on the target power equipment according to the equipment data of the target power equipment, and obtaining a corresponding feature evaluation value;

[0162] Step 3: Comprehensive Analysis

[0163] According to the state change evaluation value P1, load fluctuation evaluation value P2, and aging evaluation value P3 of the target power equipment, a comprehensive score analysis is performed on the target power equipment, and a comprehensive score coefficient of the target power equipment is obtained;

[0164] Step 4: Evaluate Management Unit

[0165] Determine and generate different risk signals based on the comprehensive score coefficient of the target power equipment;

[0166] Step 5: Results display

[0167] Different risk signals are displayed to relevant operation and maintenance personnel, who take different management measures to manage the target power equipment based on the corresponding risk signals.

[0168] The present invention also provides an electric power equipment asset management device, the device comprising a sensor module, a central processor and a display, the device is used in the electric power equipment asset management system;

[0169] The sensor module is used to realize the function of the data collection unit;

[0170] The central processing unit is used to realize the functions of the data processing unit, the comprehensive analysis unit, and the evaluation management unit;

[0171] The display is used to realize the function of the result display unit.

[0172] The present invention also provides a storage medium for an electric power equipment asset management system, wherein the storage medium is used to store all programs of the electric power equipment asset management system, and all programs are used to execute an electric power equipment asset management system.

[0173] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0174] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An electric power equipment asset management system, characterized in that: include: A data collection unit, used to collect equipment data of target power equipment, the equipment data including equipment operation information, power load information and historical fault information; A data processing unit, used to perform feature analysis on the target power equipment according to the equipment data of the target power equipment and obtain a corresponding feature evaluation value; A comprehensive analysis unit, used to perform a comprehensive score analysis on the target power equipment according to the state change evaluation value, load fluctuation evaluation value, and aging evaluation value of the target power equipment, and obtain a comprehensive score coefficient of the target power equipment; An assessment management unit, used to determine and generate different risk signals based on the comprehensive score coefficient of the target power equipment; The result display unit is used to display different risk signals to relevant operation and maintenance personnel, and the relevant operation and maintenance personnel take different management measures to manage the target power equipment according to the corresponding risk signals.

2. The power equipment asset management system according to claim 1, characterized in that: in, The equipment operation information is the operation parameters of various attributes obtained by real-time monitoring of the target power equipment through preset sensors, including but not limited to voltage, current, and power; The power load information is obtained from the corresponding monitoring equipment set up in the power system, which includes the load value at each collection time; The historical fault data is obtained from the maintenance records of the target power equipment, which includes but is not limited to the number of faults of the target power, the time of each fault, and the total operating time of the target power equipment.

3. The power equipment asset management system according to claim 2, characterized in that: in, Feature analysis includes: state change analysis, load fluctuation analysis and equipment aging analysis; Feature evaluation values ​​include: A state change evaluation value obtained by state change analysis; Load fluctuation evaluation value obtained by load fluctuation analysis; Aging assessment value obtained from equipment aging analysis.

4. The power equipment asset management system according to claim 3, characterized in that: The state change analysis method is as follows: StepA1. Select an operating parameter corresponding to an attribute; In multiple continuous collection cycles, extract the operating parameters of the attribute corresponding to n collection time nodes and mark them as D according to the time trend. i，j , i = 1, 2, ... n, j = 1, 2, ... m, m represents the number of multiple acquisition cycles; Step A2: Collect the rated parameters of the target power equipment at the same time, including but not limited to rated voltage, rated current, and rated power, and then mark them as DE j ; Among them, the rated parameters are extracted from the nameplate of the target power equipment; Step A3, through Calculate the fluctuation coefficient K of the attribute in each collection cycle j ; StepA4, through Calculate the change rate K0 between each fluctuation coefficient of the attribute in all adjacent acquisition cycles; Among them, K j and K j+1 The relationship between refers to the individual fluctuation coefficients in adjacent acquisition cycles; StepA5: Calculate the change rate of each fluctuation coefficient of each attribute in all adjacent acquisition cycles according to the method of StepA1 to StepA4, and record it as K0 t , t = 1, 2, ... e, e represents the number of various attributes in the device data; StepA6. Pass Calculate the state change evaluation value P1 of the target power equipment; In the formula, α t , β1 and β2 are the corresponding preset weight factors, K0 e It is represented as the last collection period among multiple consecutive collection periods according to the time trend, and the time interval between the last collection period and the current time node is the smallest.

5. The power equipment asset management system according to claim 4, characterized in that: The load fluctuation analysis method is as follows: Step B1, selecting a collection cycle from multiple consecutive collection cycles; Extract the load values ​​at n acquisition moments and mark them as F according to the time trend i , i=1, 2, ... n; Step B2, obtain the load values ​​at n acquisition moments and mark them as FP; Step B3, through Calculate the load fluctuation assessment value P2 corresponding to the n collection moments in the collection cycle.

6. The power equipment asset management system according to claim 5, characterized in that: The equipment aging analysis method is as follows: Step C1, obtain the number of faults of the target power equipment and mark it as r; At the same time, the total operating time of the equipment is marked as Y; Step C1, obtaining the corresponding fault occurrence time of each fault of the target power equipment; Then, according to the time when the fault occurs and the trend of time, the fault time intervals between two adjacent faults are obtained and marked as Sg, where g=1, 2, ... r-1; Step C3, through The corresponding aging assessment value P3 of the target electric equipment is calculated.

7. The power equipment asset management system according to claim 6, characterized in that: The comprehensive score analysis method is to obtain the comprehensive score coefficient Z of the target power equipment through: Z = λ1×P1+λ2×P2+λ2×P3; The evaluation management unit determines the following: Compare the comprehensive score coefficient Z of the target power equipment with the preset score determination thresholds My1, My2 and My3: wherein My1<My2<My3; If Z<My1, a low-risk signal is generated for the target power equipment, which indicates that the equipment is in good condition; If My1≤Z<My2, a medium risk signal is generated for the target power equipment, and the medium risk signal indicates that the equipment status is general; If Z≥My3, a high-risk signal is generated for the target power equipment, and the high-risk signal indicates that the state of the target power equipment is poor.

8. A method for managing power equipment assets, characterized in that: The method is implemented by an electric power equipment asset management system as described in any one of claims 1-7.

9. An electric power equipment asset management device, comprising a sensor module, a central processing unit and a display, characterized in that: The device is used to implement an electric power equipment asset management system as described in any one of claims 1 to 7; The sensor module is used to realize the function of the data collection unit; The central processing unit is used to realize the functions of the data processing unit, the comprehensive analysis unit, and the evaluation management unit; The display is used to realize the function of the result display unit.

10. A storage medium for an electric power equipment asset management system, characterized in that: The storage medium is used to store all programs of the power equipment asset management system, and all programs are used to implement the functions of the power equipment asset management system described in any one of claims 1-7.

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