Protection equipment health state scoring system and method

Abstract

The invention discloses a protection equipment health state scoring system and method, and relates to the technical field of power system relay protection equipment. The protection equipment health state scoring system comprises a secondary equipment ledger library, a scoring engine, a finite-state machine and a scoring pipeline management module. The secondary equipment ledger library is used for storing ledger information of the protection equipment; the scoring engine constructs an evaluation model according to the standing book information so as to score the protection equipment; the finite-state machine judges the health state of the protection equipment according to the score data; the score flow management module records and stores score data so as to analyze the change trend of the health state of the protection equipment; the system can also perform score adding or score deduction processing on the protection equipment so as to adjust the evaluation result of the health state of the protection equipment. According to the protection equipment health state scoring system and method provided by the invention, the health state of the protection equipment can be accurately evaluated, accurate and timely maintenance is realized, and the operation reliability and stability of a power grid are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of relay protection equipment in power systems, and in particular to a protection equipment health status scoring system and method. Background Art

[0002] Relay protection equipment is used to protect electrical equipment and ensure the safe and stable operation of the power system. Its reliability is closely related to the safe operation of the power grid. In recent years, with the continuous acceleration of the construction of smart substations, the number of relay protection equipment has also increased day by day.

[0003] The traditional operation and maintenance mode of relay protection equipment includes regular maintenance and emergency repair; regular maintenance requires comprehensive inspection, testing and maintenance of relay protection equipment according to the predetermined maintenance plan and cycle; fault repair is to quickly organize personnel to carry out emergency repairs when the relay protection equipment fails. With the increase in the number of relay protection equipment, if the old operation and maintenance mode is continued, it will lead to high cost and low efficiency problems; therefore, it is very necessary to grasp the operating status of protection equipment in real time and accurately evaluate the health status of equipment to strengthen the refined management of equipment, guide targeted operation and maintenance activities, and thus improve the reliability and stability of power grid operation. Summary of the invention

[0004] The present invention provides a protection equipment health status scoring system and method, which aims to accurately evaluate the health status of relay protection equipment and improve the operational reliability and stability of the power grid.

[0005] The protection equipment health status scoring system provided by the present invention includes:

[0006] The secondary equipment ledger library is used to store the ledger information of the protection equipment, which includes the basic information of the protection equipment and the information of the full time and space process;

[0007] A scoring engine, used to obtain the ledger information and build an evaluation model based on the ledger information to score the protection equipment and obtain scoring data of the protection equipment;

[0008] A finite state machine, configured to receive the scoring data and determine a health status of a protection device according to the scoring data;

[0009] The scoring pipeline management module is used to record the scoring data and store the scoring data in a database.

[0010] Optionally, the scoring pipeline management module is also used to detect changes in the ledger information and drive the evaluation model to re-score the protection equipment to obtain new evaluation results.

[0011] Optionally, the finite state machine includes a state transfer logic module;

[0012] The state transfer logic module is used to drive the scoring engine to add or deduct points from the scoring data according to the new evaluation result;

[0013] The state transfer logic module is also used to adjust the judgment result of the health status of the protection device according to the scoring data after the score addition or deduction processing.

[0014] Optionally, the system further comprises:

[0015] The scoring warning module is used to send out a scoring warning signal when the scoring engine performs scoring processing on the scoring data.

[0016] Optionally, the system further comprises:

[0017] User interface, used for visual display and human-computer interactive operation.

[0018] Optionally, the full-time and space process information includes at least one of pre-production hidden dangers, equipment service life, defect hidden dangers, countermeasure execution status, incorrect protection action status, family defects, equipment maintenance history, equipment failure status, plug-in damage records, spare parts redundancy, and manufacturer service evaluation.

[0019] The protection equipment health status scoring method provided by the present invention comprises the following steps:

[0020] S1, obtaining the record information of the protection device, wherein the record information includes the basic information of the protection device and the full-time and space process information;

[0021] S2, constructing an evaluation model based on the ledger information, and constructing a scoring engine according to the evaluation model;

[0022] S3, scoring the protection device through the scoring engine to obtain scoring data of the protection device;

[0023] S4, inputting the scoring data into a finite state machine, and determining the health status of the protection device according to the scoring data;

[0024] S5, detecting changes in the ledger information, and driving the evaluation model to re-score the protection device, and then adding or deducting points from the scoring data through the scoring engine;

[0025] S6, adjusting the judgment result of the finite state machine on the health status of the protection device according to the change of the scoring data.

[0026] Optionally, the step S2 specifically includes the following steps:

[0027] Divide the full-time and space process information of the protection equipment into multiple levels, construct a multi-level model, and determine the evaluation scale of each level of indicators in the multi-level model;

[0028] Create a judgment matrix to quantify the relative weights between indicators at each level in the multi-level model. ,Right now:

[0029]

[0030] In the formula, ; Among them, a ij Indicates the comparison result of index i and index j, a ji represents the comparison result of indicators j and i, and n is the number of indicators in the judgment matrix;

[0031] Calculating the eigenvector and the maximum eigenvalue of the judgment matrix to determine the weights of the indicators at each level in the multi-level model;

[0032] The weights of indicators at all levels and their indicator scores are multiplied and weighted summed to obtain the scoring data of the protection equipment.

[0033] Optionally, the step of calculating the eigenvector and the maximum eigenvalue of the judgment matrix to determine the weights of the indicators at each level in the multi-level model further includes:

[0034] Calculate the consistency index CI of the judgment matrix, CI satisfies:

[0035]

[0036] In the formula, is the maximum eigenvalue of the judgment matrix;

[0037] Calculate the random consistency ratio CR of the judgment matrix according to the consistency index CI of the judgment matrix, CR=CI / RI, where RI is the average consistency index of the judgment matrix;

[0038] When the random consistency ratio CR of the judgment matrix is ​​less than 0.1, it is determined that the judgment matrix passes the consistency test, that is, meets the consistency requirement, and the weight vector of any indicator is solved by the following formula:

[0039]

[0040] Where ω is the weight vector;

[0041] The solved weight vector is normalized to obtain the weight of the corresponding indicator.

[0042] The present invention also provides a computer device, the computer device comprising a memory and a processor;

[0043] The memory stores a computer program;

[0044] When the processor executes the computer program, the steps of the above-mentioned method for scoring the health status of the protection device are implemented.

[0045] It can be seen from the above technical solutions that the present invention has the following beneficial effects:

[0046] The technical solution of the present invention analyzes the factors that affect the healthy operation of protection equipment, constructs a full-time and space multi-parameter equipment risk assessment model including indicators such as pre-production hidden dangers, equipment service life, defect hidden dangers, countermeasure execution status, incorrect protection action status, family defects, spare parts redundancy, etc., and scores the health status of the protection equipment by analyzing the massive operation and maintenance data of the protection equipment throughout its life cycle; when the evaluation index of the protection equipment changes, the scoring engine is driven to add or deduct points from the score of the protection equipment, so as to timely reflect the changes in the health status of each protection equipment, and further provide early warnings and suggestions to the operation and maintenance personnel, so as to realize accurate and timely maintenance of the power grid relay protection equipment, thereby improving the operational reliability and stability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0048] Figure 1 It is a structural block diagram of the health status scoring system of the protection equipment of the present invention;

[0049] Figure 2 This is a schematic diagram of a health status assessment model for protection equipment of the present invention;

[0050] Figure 3 A schematic diagram of a data-driven protection equipment health status assessment and decision-making framework of the present invention;

[0051] Figure 4 This is a schematic diagram of the decomposition of the health status evaluation factors of the protection equipment of the present invention;

[0052] Figure 5 This is an implementation effect diagram of an embodiment of a protection device health status scoring system of the present invention;

[0053] Figure 6 It is a data collection block diagram of an embodiment of a protection device health status scoring system of the present invention;

[0054] Figure 7 The figure is a flowchart of the method for scoring the health status of protection equipment of the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below 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.

[0056] The present invention proposes a protection device health status scoring system and method, aiming to accurately evaluate the health status of relay protection equipment (hereinafter referred to as protection equipment) and improve the operational reliability and stability of the power grid.

[0057] See also Figure 1 In one embodiment, the protection device health status scoring system proposed by the present invention includes:

[0058] The secondary equipment ledger database is used to store the ledger information of the protection equipment, which includes the basic information of the protection equipment and the full-time and space process information;

[0059] The scoring engine is used to obtain the ledger information and build an evaluation model based on the ledger information to score the protection equipment and obtain the scoring data of the protection equipment;

[0060] A finite state machine, used for receiving the scoring data and determining the health status of the protection device according to the scoring data;

[0061] The scoring pipeline management module is used to record the scoring data and store the scoring data in the database.

[0062] In this embodiment, the basic information of the protection device includes the name, model, manufacturer, factory serial number, installation location, technical parameters, operation information, maintenance information, etc. of the device.

[0063] Among them, the technical parameters of the protection equipment include the equipment's rated voltage, rated current, action setting, action time, accuracy level, etc. The operation information of the protection equipment includes the equipment's operation date, operation status, number of actions, the time of the most recent calibration, etc. The maintenance information of the protection equipment includes the maintenance cycle, maintenance content, maintenance personnel, etc.

[0064] In this embodiment, the full-time and space process information includes one or more of pre-production hidden dangers, equipment service life, defect hidden dangers, countermeasure execution status, incorrect protection action status, family defects, equipment maintenance history, equipment failure status, plug-in damage records, spare parts redundancy, and manufacturer service evaluation.

[0065] Among them, pre-production hidden dangers and defect hidden dangers refer to the deficiencies of protection equipment in equipment quality, installation and commissioning, environmental factors, personnel management, etc. before and after production respectively; family defects refer to similar defects in multiple protection devices produced by the same batch, the same model or the same manufacturer due to common factors such as design, material, and process; spare parts redundancy refers to the proportional relationship between the number of spare parts prepared to ensure that the power system can still operate normally in the event of equipment failure or maintenance and the actual demand quantity, which has a direct impact on system reliability, maintenance time and equipment upgrades and modifications; manufacturer service evaluation includes the manufacturer's technical support, response speed and service quality before, during and after sales, as well as customer satisfaction and industry reputation.

[0066] In this embodiment, the secondary equipment inventory library stores inventory information of the entire life cycle of the protection equipment. Therefore, the evaluation model constructed based on the inventory information is a full-time and space multi-parameter evaluation model, which is composed of evaluation objects, evaluation parameters, and judgment basis.

[0067] See also Figure 2 The evaluation object is a specific protection device. The system selects appropriate evaluation parameters based on multi-dimensional data such as operating time, operation and maintenance status, regular inspection data, countermeasures, and protection actions. The judgment basis is established through the evaluation index system of the protection equipment. According to the evaluation parameters, appropriate status evaluation indicators are selected, and then the importance of different status indicators is accurately and objectively evaluated to determine the weight of each status indicator. The evaluation index system can be obtained by subjective or objective weighting methods such as expert survey method and hierarchical analysis method.

[0068] Among them, the evaluation parameters need to be selected by comprehensively considering real-time, historical and other factors, see Figure 4 , Figure 4 An example of decomposition of factors for evaluating the health status of protection equipment is given. Real-time factors include operating conditions, communications and circuits, equipment performance, etc. Historical factors include equipment aging, equipment operation and maintenance, equipment failure, etc. Other factors include equipment importance, resource factors and manufacturer factors, etc., and evaluation parameters are further refined based on these factors; for example, operating conditions can be further refined into parameters such as ambient temperature, CPU temperature, equipment voltage, and optical port temperature; these real-time, historical and other factor parameter data are stored in the secondary equipment ledger library.

[0069] See also Figure 2In a preferred embodiment, the evaluation index system can be obtained by the hierarchical analysis method, that is, the equipment health status evaluation index is divided into multiple levels, the specific index weights and values ​​of each level are summarized, and then the scoring data of the corresponding protection equipment is calculated by a suitable algorithm.

[0070] Furthermore, the output of the evaluation model is quantified to build a protection equipment scoring engine.

[0071] Among them, the output of the evaluation model is quantified, that is, each state indicator in the quantified evaluation model is converted into a specific value; the quantified indicator value can be an absolute value or a relative value. For example, for the response time of the equipment, the specific time value can be obtained through actual testing. For the anti-interference ability of the equipment, a relative anti-interference ability index can be obtained by quantitatively evaluating the performance under different interference intensities; according to the quantified state indicator value and the corresponding weight, the comprehensive score of the protection equipment is calculated; the scoring algorithm can be a weighted summation method or a more complex mathematical model, depending on the evaluation requirements and the characteristics of the data.

[0072] The scoring engine needs to receive the evaluation results of the evaluation model and process and calculate them.

[0073] For example, for the input equipment operation data, the scoring engine can perform data screening, outlier processing, trend analysis and other operations to ensure the accuracy and reliability of the data; the output result of the scoring engine is a clear protection equipment score value, and it can also provide some auxiliary information, such as the scores of each indicator, the basis and explanation of the scoring, etc.

[0074] Furthermore, based on the above evaluation model and scoring engine, a finite state machine is constructed; the finite state machine corresponds the state of the protection device to a fixed scoring interval one by one.

[0075] In a preferred embodiment, the finite state machine divides the status of the protection equipment into: normal, regular inspection, modification, and special maintenance; normal means that the equipment does not require special treatment, regular inspection means that a regular inspection plan for the equipment needs to be arranged, modification means that the equipment needs to be modified and put into storage, and special maintenance means that the maintenance level of the equipment needs to be improved.

[0076] Furthermore, based on the above-mentioned evaluation model and scoring engine, a scoring flow management module is built to record and manage various data and operation flows in the scoring process; the scoring flow data provides a rich resource for data analysis, and the scoring data can be statistically analyzed to understand the overall performance status of the protection equipment, the scoring differences of different types of equipment, the scoring trends, etc., and then analyze the changing trends of the health status of the protection equipment, which can provide a basis for the improvement and optimization of the protection equipment, and also help to formulate more scientific and reasonable scoring standards and management strategies.

[0077] In this embodiment, the integration and collaborative work of different modules or units can be achieved through an application programming interface (API).

[0078] The embodiment of the present invention analyzes the factors that affect the healthy operation of the protection equipment and constructs a full-time and space multi-parameter equipment risk assessment model including indicators such as pre-production hidden dangers, equipment service life, defect hidden dangers, countermeasure execution status, incorrect protection action status, familial defects, and spare parts redundancy. By analyzing the massive operation and maintenance data of the protection equipment throughout its life cycle, the health status of the protection equipment can be accurately scored, which can achieve a scientific, objective and accurate evaluation of the protection equipment, and provide strong support for equipment selection, operation and maintenance, and management decisions.

[0079] Based on the above embodiments, further, refer to Figure 3 In one embodiment, the scoring pipeline management module is also used to detect changes in ledger information, or to detect changes in data in any dimension, and drive the evaluation model to re-score the protection equipment to obtain new evaluation results.

[0080] Specifically, when there is a change in the data of any dimension, such as hidden dangers before production, service life of equipment, defect hidden dangers, countermeasure execution status, incorrect protection action status, family defects, spare parts redundancy, manufacturer service evaluation, etc., it will automatically drive a scoring pipeline task, triggering a new round of evaluation.

[0081] In some other embodiments, when the device inspection results change, the protection device health status scoring system automatically triggers a new scoring pipeline task based on the remote inspection results; when the protection device has a program version update, a new scoring pipeline task is also automatically triggered.

[0082] See also Figure 3 ,Further, in one embodiment, the finite state machine includes a state transfer logic module;

[0083] The state transfer logic module is used to drive the scoring engine to add or deduct points from the scoring data of the protection device according to the new evaluation results;

[0084] The state transfer logic module is also used to adjust the judgment result of the health status of the protection device according to the scoring data after the addition or deduction of points.

[0085] In this embodiment, the state transfer logic module includes a state transfer rule base; the evaluation module maps the new evaluation results of the protection device to the state transfer logic module, and by traversing and matching the rules of the state transfer rule base, when the corresponding rules are met, it will trigger the modification of the rating value of the protection device based on the evaluation results, that is, add or deduct points from the rating data of the protection device; the state transfer rule base is an expression system containing variables, which can dynamically add, adjust, and delete rules. When the score satisfies the state change, it will trigger the change of the target state of the protection device. When the score does not satisfy the state change, the protection device maintains its original state.

[0086] In a specific implementation, taking hidden danger countermeasures as an example, when important countermeasures are not carried out, the score of the protection equipment will be deducted by 10 points for every month that passes. The following rules can be constructed for this requirement:

[0087] Score=IS-10*(CT-DT) / 2592000;

[0088] Where IS represents the initial minute, CT represents the current time (in seconds), DT represents the required completion time (in seconds), and 2592000 represents one natural month (the total time of 30 days, in seconds).

[0089] In this embodiment, the evaluation model and the finite state machine can be further combined. The evaluation model is first used to evaluate the performance and reliability of each state, and then the evaluation model is embedded in the finite state machine to form a more complete state transition condition rule.

[0090] Specifically, performance indicators such as response time, accuracy, and stability can be considered; reliability indicators such as failure rate, mean time between failures, and maintainability can be considered; by measuring and analyzing these indicators, the specific performance of the equipment in various states can be obtained; for example, under normal operating conditions, the evaluation model can monitor the equipment's output signal, response time and other parameters to evaluate whether its performance meets the requirements; under fault conditions, the reliability of the equipment can be evaluated by analyzing factors such as the fault type and the frequency of fault occurrence.

[0091] Furthermore, by evaluating the performance and reliability of the device in different states, it can be determined whether the state is stable or needs to be transferred, and under what circumstances the state transfer should be performed.

[0092] In the traditional state machine model, the state transition conditions are only based on some simple logical judgments, such as the appearance or disappearance of a fault signal; in this embodiment, the finite state machine is combined with the evaluation model to determine the state transition conditions based on the performance and reliability indicators of the protection equipment, to consider the operating status of the protection equipment more comprehensively, and to combine the target state of the protection equipment with the maintenance conditions to achieve precise maintenance.

[0093] In a specific implementation, if the evaluation model finds that the performance of the equipment in a certain state has a significant downward trend, the state transition condition can be triggered in advance to put the equipment into a maintenance state (regular inspection, transformation, special maintenance) for preventive maintenance to avoid failures.

[0094] In another specific embodiment, based on the performance of the equipment in different states and the frequency of failures, it can be determined which components require focused maintenance and which maintenance measures are effective, thereby improving the efficiency and quality of maintenance work.

[0095] participate Figure 1 and Figure 3 In one embodiment, the protection device health status scoring system further includes: a deduction warning module, which is used to issue a deduction warning signal when the scoring engine performs a deduction process on the scoring data.

[0096] Specifically, when the scoring pipeline management module drives a new scoring pipeline task, it triggers a new round of evaluation of the protection equipment. Combined with the evaluation module and the state transfer logic module, it triggers the modification of the scoring data of the protection equipment. When deductions occur, the deduction warning module automatically identifies and issues a corresponding deduction warning signal to remind the operator to pay attention to the equipment's scoring status and make suggestions for maintenance, modification or special maintenance.

[0097] In a preferred embodiment, after countermeasures, regular inspections or version updates, the protection device health status scoring system will issue a point deduction warning for related unprocessed devices, reminding operators to deal with them in time, otherwise the point deduction will continue over time.

[0098] Based on the above embodiments, in order to facilitate operators to manage and maintain secondary equipment ledgers, basic information, process data, and visualize equipment evaluation results, deduction warnings, etc., in one embodiment, the protection equipment health status scoring system also includes: a user interface for visual display and human-computer interaction.

[0099] See also Figure 5In a specific implementation, the user interface includes at least a warning section for deduction of points, score management, and basic information maintenance, and can visually display the statistical results of the scores and health status of the protection equipment through statistical graphs and tables, and give obvious marks and maintenance suggestions for equipment to be repaired, to be modified, to be specially maintained, to be inspected, etc.; the user interface can also set operation and maintenance information query conditions, such as equipment operation and maintenance department, operation and maintenance center, substation voltage level, substation, etc., and input query conditions to quickly check the health status of specific protection equipment and operation and maintenance areas.

[0100] Based on the above embodiments, see Figure 6 In a specific embodiment of a power system, the relay protection device is connected to the intelligent recorder through the IEC61850 protocol. The intelligent recorder, as a client, accesses the relay protection device, obtains real-time status information such as operating conditions, communications and circuits, and sends it to the main station system in zone I. Finally, the real-time data is aggregated to the system in zone III through the isolation device; historical information such as ledgers, equipment operation and maintenance records, etc. are manually entered in the system in zone III or imported from other equipment management systems.

[0101] In this embodiment, when the system is operating normally, the intervals and devices are queried based on the equipment operation and maintenance department, patrol and maintenance center, substation voltage level, and substation as query conditions; the health of the intervals and devices is scored and counted through the scoring engine; the statistical results are visualized in the form of graphics or lists for equipment awaiting maintenance, special maintenance, modification, and scheduled inspection.

[0102] In this embodiment, when any dimension of data changes, such as hidden dangers before the protection equipment is put into production, service life of the equipment, defect hidden dangers, countermeasure execution status, incorrect protection action status, family defects, spare parts redundancy, manufacturer service evaluation, changes in inspection results, program version updates, etc., the system automatically triggers a new scoring pipeline task and drives the scoring engine to conduct a new round of evaluation of the protection equipment.

[0103] It can be seen from the above embodiments that the protection equipment health status scoring system proposed in the present invention constructs a full-time and space multi-parameter equipment risk assessment model including pre-commissioning hidden dangers, equipment service life, defect hidden dangers, countermeasure execution status, incorrect protection action status, family defects, and spare parts redundancy by analyzing the factors affecting the healthy operation of the protection equipment; the system is composed of secondary equipment ledger library, scoring engine, scoring flow management, secondary equipment state machine, deduction warning and other modules; by analyzing the massive operation and maintenance data of the protection equipment throughout its life cycle, the protection equipment is scored by comprehensively considering real-time, historical and other factors. When the evaluation parameters of the protection equipment change, the scoring engine is driven to add or deduct points for the equipment; according to the scoring results, the judgment results of the health status of the protection equipment such as normal, maintenance, transformation, special maintenance, etc. are given, and combined with the evaluation model and the state transition logic module, a more complete state transition rule is constructed, which can realize accurate maintenance of the protection equipment, thereby improving the reliability and stability of the power grid.

[0104] Based on the above embodiment of the protection device health status scoring system, the present invention also proposes a protection device health status scoring method.

[0105] See also Figure 7 In one embodiment, the method comprises the following steps:

[0106] S1, obtain the ledger information of the protection equipment, which includes the basic information of the protection equipment and the full-time and space process information;

[0107] S2, builds an evaluation model based on the ledger information, and builds a scoring engine based on the evaluation model;

[0108] S3, scoring the protection device through a scoring engine to obtain scoring data of the protection device;

[0109] S4, inputting the scoring data into a finite state machine, and determining the health status of the protection device according to the scoring data;

[0110] S5, detecting changes in the ledger information, and driving the evaluation model to re-score the protection device, and then adding or deducting points from the scoring data through the scoring engine;

[0111] S6, adjusting the judgment result of the finite state machine on the health status of the protection device according to the change of the scoring data.

[0112] In order to realize the construction of the evaluation model in the above embodiment, in one embodiment, step S2 specifically includes the following steps:

[0113] Divide the evaluation indicators of protection equipment into multiple levels, construct a multi-level model, and determine the evaluation scale of each level of indicators in the multi-level model;

[0114] In one implementation, the health evaluation indicators of the protection equipment are divided into three levels, namely, the target level (relay protection equipment), the criterion level (intermediate indicators), and the scheme level (detailed indicators); a hierarchical model including 9 first-level indicators and 34 second-level indicators is further constructed, as shown in Table 1.

[0115]

[0116] Table 1 Evaluation index system for relay protection equipment

[0117] Furthermore, a judgment matrix is ​​created to quantify the relative weights between indicators at each level in the above multi-level model; the comparison matrix is ​​a square matrix whose elements represent the relative importance between two factors, usually represented by a scale of 1-9, where 1 means that the two factors are equally important, and 9 means that one factor is much more important than the other (the scale can be obtained through multiple rounds of adjustments based on industry experience through the Delphi method), see Table 2.

[0118] Let X = (x1, x2, ..., x n ) is the set of all influencing factors, and all indicators are correlated with each other to construct a judgment matrix ,Right now:

[0119]

[0120] In the formula, ; Among them, a ij Indicates the comparison result of index i and index j, a ji represents the comparison result of indicators j and i, and n is the number of indicators in the judgment matrix;

[0121] Furthermore, the eigenvector and the maximum eigenvalue of the judgment matrix are calculated to determine the weights of the indicators at each level in the multi-level model.

[0122] Among them, the eigenvector is a column vector whose elements represent the relative weights of factors at all levels; the maximum eigenvalue represents the consistency of the comparison matrix; if the consistency index exceeds 0.1, the comparison judgment matrix needs to be re-evaluated.

[0123] Specifically, it is necessary to calculate the consistency index CI of the judgment matrix, and CI satisfies:

[0124]

[0125] In the formula, is the maximum eigenvalue of the judgment matrix;

[0126] Calculate the random consistency ratio CR of the judgment matrix according to the consistency index CI of the judgment matrix, CR=CI / RI, where RI is the average consistency index of the judgment matrix;

[0127] When the random consistency ratio CR of the judgment matrix is ​​less than 0.1, it is determined that the judgment matrix passes the consistency test, that is, meets the consistency requirement, and the weight vector of any indicator is solved by the following formula:

[0128]

[0129] In the formula, ω is the weight vector; the weight vector obtained by solving is normalized to obtain the weight of the corresponding indicator.

[0130] Finally, the weights of indicators at all levels and their indicator scores are multiplied and weighted summed to obtain the scoring data of the protection equipment.

[0131]

[0132] Table 2 Evaluation scale

[0133] The embodiment of the above method, based on the protection equipment health status scoring system, elaborates in detail the construction process of the protection equipment evaluation index system; based on the evaluation index system, the weight of each status indicator can be determined, and then the evaluation model can be constructed in combination with the quantification rules of each status indicator to generate scoring data for the protection equipment health status evaluation; as long as the importance of different indicators can be accurately and objectively judged, the evaluation model based on quantitative behavior of the present invention also has corresponding accuracy and objectivity, thereby providing operators with accurate, timely and intuitive protection equipment health status information, thereby realizing accurate and timely maintenance of power grid relay protection equipment.

[0134] The present invention also provides a computer device, which includes a memory and a processor; the memory stores a computer program; when the processor executes the computer program, the steps of the protection device health status scoring method described in the aforementioned embodiment are implemented; therefore, the technical effects that can be achieved by the protection device health status scoring method provided in the aforementioned embodiment can also be achieved by the computer device, which will not be repeated here.

[0135] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the computer program can be stored in a readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory.

[0136] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A protection equipment health status scoring system, characterized in that: The system comprises: The secondary equipment ledger library is used to store the ledger information of the protection equipment, which includes the basic information of the protection equipment and the full-time and space process information; A scoring engine, used to obtain the ledger information and build an evaluation model based on the ledger information to score the protection equipment and obtain scoring data of the protection equipment; A finite state machine, configured to receive the scoring data and determine a health status of a protection device according to the scoring data; The scoring pipeline management module is used to record the scoring data and store the scoring data in a database.

2. The protection device health status scoring system according to claim 1, characterized in that: The scoring pipeline management module is also used to detect changes in the ledger information and drive the evaluation model to re-evaluate the protection equipment to obtain new evaluation results.

3. The protection device health status scoring system according to claim 2, characterized in that: The finite state machine includes a state transfer logic module; The state transfer logic module is used to drive the scoring engine to add or deduct points from the scoring data according to the new evaluation result; The state transfer logic module is also used to adjust the judgment result of the health status of the protection device according to the scoring data after the score addition or deduction processing.

4. The protection device health status scoring system according to claim 3, characterized in that: The system further comprises: The scoring warning module is used to send out a scoring warning signal when the scoring engine performs scoring processing on the scoring data.

5. The protection device health status scoring system according to claim 1, characterized in that: The system further comprises: User interface, used for visual display and human-computer interactive operation.

6. The protection device health status scoring system according to any one of claims 1 to 5, characterized in that: The full-time and space process information includes at least one of pre-production hidden dangers, equipment service life, defect hidden dangers, countermeasure execution status, incorrect protection action status, family defects, equipment maintenance history, equipment failure status, plug-in damage records, spare parts redundancy, and manufacturer service evaluation.

7. A method for scoring the health status of a protection device, characterized in that: The method comprises the steps of: S1, obtaining the record information of the protection device, wherein the record information includes the basic information of the protection device and the full-time and space process information; S2, constructing an evaluation model based on the ledger information, and constructing a scoring engine according to the evaluation model; S3, scoring the protection device through the scoring engine to obtain scoring data of the protection device; S4, inputting the scoring data into a finite state machine, and determining the health status of the protection device according to the scoring data; S5, detecting changes in the ledger information, and driving the evaluation model to re-score the protection device, and then adding or deducting points from the scoring data through the scoring engine; S6, adjusting the judgment result of the finite state machine on the health status of the protection device according to the change of the scoring data.

8. The method according to claim 7, characterized in that The step S2 specifically includes the following steps: Divide the full-time and space process information of the protection equipment into multiple levels, construct a multi-level model, and determine the evaluation scale of each level of indicators in the multi-level model; Create a judgment matrix to quantify the relative weights between indicators at each level in the multi-level model. ,Right now: In the formula, ; Among them, a ij Indicates the comparison result of index i and index j, a ji represents the comparison result of indicators j and i, and n is the number of indicators in the judgment matrix; Calculating the eigenvector and the maximum eigenvalue of the judgment matrix to determine the weights of the indicators at each level in the multi-level model; The weights of indicators at all levels and their indicator scores are multiplied and weighted summed to obtain the scoring data of the protection equipment.

9. The method according to claim 8, characterized in that The step of calculating the eigenvector and the maximum eigenvalue of the judgment matrix to determine the weights of the indicators at each level in the multi-level model also includes: Calculate the consistency index CI of the judgment matrix, CI satisfies: In the formula, is the maximum eigenvalue of the judgment matrix; Calculate the random consistency ratio CR of the judgment matrix according to the consistency index CI of the judgment matrix, CR=CI / RI, where RI is the average consistency index of the judgment matrix; When the random consistency ratio CR of the judgment matrix is ​​less than 0.1, it is determined that the judgment matrix meets the consistency requirement, and the weight vector of any indicator is solved by the following formula: Where ω is the weight vector; The solved weight vector is normalized to obtain the weight of the corresponding indicator.

10. A computer device, characterized in that: including memory and processor; The memory stores a computer program; When the processor executes the computer program, the steps of the protection device health status scoring method according to any one of claims 7 to 9 are implemented.

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