A power grid equipment fault risk monitoring and early warning system

Abstract

The present invention provides a power grid equipment fault risk monitoring and early warning system, belonging to the technical field of power grid equipment monitoring, including: a first acquisition module: acquiring the type and characteristics of power grid equipment, and acquiring the real-time status of power grid equipment according to the type and characteristics of power grid equipment; a second acquisition module: acquiring the reliability status of power grid equipment, and using a logical decision-making method in combination with the real-time status to acquire the maintenance-related information of power grid equipment; a determination module: acquiring the surrounding environment parameters of power grid equipment, combining the maintenance-related information to perform maintenance on power grid equipment, and determining the fault risk of power grid equipment; a grading module: grading the fault risk and giving an early warning; a repair module: acquiring the corresponding repair strategy according to the early warning result, and repairing the power grid equipment fault based on the repair strategy. It solves the problem that the real-time operation status of power grid equipment cannot be monitored, resulting in the inability to respond to equipment anomalies in a timely manner, reducing the reliability and monitoring lean level of the equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid equipment monitoring, and particularly to a power grid equipment fault risk monitoring and early warning system. Background Art

[0002] With the rapid development of China's power system, the number and types of power grid equipment are constantly increasing. At the same time, since the safe operation of power grid equipment is directly related to people's life and property safety, the monitoring and early warning work of fault risks has been increasingly emphasized.

[0003] Existing power grid equipment fault risk early warning systems may not be able to monitor the real-time operation status of power grid equipment, resulting in the inability to respond to equipment abnormalities in a timely manner. At the same time, traditional monitoring and early warning systems lack sufficient intelligent capabilities and are difficult to identify complex fault modes, reducing the reliability of equipment and the lean level of monitoring, and unable to ensure the operation and maintenance efficiency and cost control of equipment.

[0004] Therefore, the present invention proposes a power grid equipment fault risk monitoring and early warning system. Summary of the Invention

[0005] The present invention provides a power grid equipment fault risk monitoring and early warning system to solve the defects in the prior art that the real-time operation status of power grid equipment cannot be monitored, resulting in the inability to respond to equipment abnormalities in a timely manner. At the same time, traditional monitoring and early warning systems lack sufficient intelligent capabilities and are difficult to identify complex fault modes, reducing the reliability of equipment and the lean level of monitoring, and unable to ensure the operation and maintenance efficiency and cost control of equipment.

[0006] On the one hand, the present invention provides a power grid equipment fault risk monitoring and early warning system, which is characterized by including:

[0007] The first acquisition module: acquires the type and characteristics of power grid equipment, and based on the type and characteristics of the power grid equipment, acquires the real-time status of the power grid equipment through corresponding sensors;

[0008] The second acquisition module: acquires the reliability status of the power grid equipment, and combines the real-time status to obtain the maintenance-related information of the power grid equipment by using a logical decision-making method;

[0009] The determination module: acquires the surrounding environment parameters of the power grid equipment, performs maintenance on the power grid equipment in combination with the maintenance-related information, and determines the fault risk of the power grid equipment according to the maintenance results;

[0010] The level division module: divides the fault risk into levels, and gives an early warning of the power grid equipment fault risk according to the division result;

[0011] The repair module: acquires the corresponding repair strategy according to the early warning result, and repairs the power grid equipment fault based on the repair strategy.

[0012] According to a power grid equipment fault risk monitoring and early warning system provided by the present invention, the first acquisition module includes:

[0013] The first determination unit: Determine multiple information of each power grid equipment through the technical manual of the power grid equipment;

[0014] The first acquisition unit: Determine the type and characteristics of the power grid equipment according to the multiple information, and acquire the indicators and parameters that need to be monitored for the power grid equipment according to the type and characteristics of the power grid equipment;

[0015] The selection unit: Select the corresponding sensors according to the indicators and parameters that need to be monitored;

[0016] The second determination unit: Acquire the real-time parameters of the power grid equipment through the sensors, and perform analysis, and determine the real-time state of the power grid equipment according to the analysis result.

[0017] According to a power grid equipment fault risk monitoring and early warning system provided by the present invention, the second acquisition module includes:

[0018] The third determination unit: Acquire the service life and historical faults of the power grid equipment according to the database, and determine the reliability status of the power grid equipment according to the service life and historical faults;

[0019] The second acquisition unit: Acquire the usage frequency and load conditions of the power grid equipment according to the reliability status of the power grid equipment;

[0020] The fourth determination unit: Determine the importance level of each power grid equipment according to the usage frequency and load conditions of the power grid equipment;

[0021] The third acquisition unit: Acquire the maintenance-related information of the power grid equipment by using the method of logical decision-making in combination with the real-time state according to the importance level of each power grid equipment.

[0022] According to a power grid equipment fault risk monitoring and early warning system provided by the present invention, the second acquisition unit includes:

[0023] The first acquisition subunit: Acquire the reliability data of the power grid equipment according to the reliability status of the power grid equipment;

[0024] The scoring subunit: Analyze the reliability data, acquire multiple indicators of the power grid equipment, and perform a reliability score on the power grid equipment according to the multiple indicators;

[0025] The classification subunit: Classify the power grid equipment according to the reliability score, and determine the time intervals for starting and stopping the power grid equipment and the grid load and equipment capacity according to the classification result;

[0026] The first determination subunit: determines the usage frequency of grid equipment according to the time interval, and determines the load condition of grid equipment according to the grid load and equipment capacity.

[0027] According to a grid equipment fault risk monitoring and early warning system provided by the present invention, a determination module includes:

[0028] The fourth acquisition unit: acquires the ambient environment parameters of grid equipment through a public data source;

[0029] The judgment unit: judges the maintenance conditions according to the ambient environment parameters, and performs maintenance on grid equipment according to the maintenance conditions and maintenance-related information;

[0030] The comparison unit: compares the obtained maintenance result with the normal operation range of the equipment to obtain abnormal values;

[0031] The analysis unit: analyzes the abnormal values, and determines the fault risk of grid equipment according to the analysis results.

[0032] According to a grid equipment fault risk monitoring and early warning system provided by the present invention, a grading module includes:

[0033] The fifth acquisition unit: analyzes the fault risk to obtain the influencing causes of the occurrence of the fault;

[0034] The evaluation unit: evaluates the influence degree on grid equipment according to the influencing causes, and grades the fault risk according to the influence degree;

[0035] The fifth determination unit: determines the early warning threshold for each level based on the type, characteristics and maintenance strategy of grid equipment;

[0036] The early warning unit: gives early warnings to the fault risks of grid equipment at different levels according to the early warning thresholds.

[0037] According to a grid equipment fault risk monitoring and early warning system provided by the present invention, a repair module includes:

[0038] The query unit: obtains early warning data according to the early warning result, queries the corresponding repair strategy database according to the early warning data, and obtains the repair strategy corresponding to the early warning data;

[0039] The extraction unit: processes the queried repair strategy, extracts the key information of the repair strategy, and generates a work guide corresponding to the repair strategy;

[0040] The repair unit: repairs the grid equipment fault based on the repair strategy and the work guide.

[0041] According to a grid equipment fault risk monitoring and early warning system provided by the present invention, a first acquisition unit includes:

[0042] The second acquisition subunit: determines multiple performance indicators of grid equipment according to types and characteristics, and acquires historical performance data of grid equipment based on the performance indicators;

[0043] The construction subunit: constructs a three-dimensional performance parameter matrix of grid equipment according to the historical performance data;

[0044] The second determination subunit: determines the deterioration data items and their deterioration parameters of grid equipment according to the three-dimensional performance parameter matrix;

[0045] The third acquisition subunit: determines the compliance characteristics of each deterioration data item according to the deterioration parameters, and acquires the mapping factors of each deterioration data item based on the compliance characteristics;

[0046] The first screening subunit: screens out potential dynamic factors from the mapping factors, and determines the main operation dynamic factors in the potential dynamic factors based on the working principle of grid equipment;

[0047] The detection subunit: detects multiple morphological mapping indicators of the main operation dynamic factors, and determines the expression level of each morphological mapping indicator for the main operation dynamic factors according to the index attributes of each morphological mapping indicator;

[0048] The second screening subunit: screens out qualified target morphological mapping indicators according to the expression level, and acquires the unit attributes of the target morphological mapping indicators;

[0049] The rating unit: determines the detection levels of each target morphological mapping indicator according to the unit attributes, rates all the target morphological mapping indicators based on the detection levels of each target morphological mapping indicator, and acquires two levels;

[0050] The third determination subunit: determines the first monitoring weight of each divided target morphological mapping indicator by using an objective weighting method for the divided target morphological mapping indicators at the first level;

[0051] The fourth determination subunit: determines the second monitoring weight of each divided target morphological mapping indicator by using a combined weighting form of subjective weighting method and objective weighting method for the divided target morphological mapping indicators at the second level;

[0052] The fifth determination subunit: determines the index description detail degree of each target morphological mapping indicator based on the first monitoring weight and the second monitoring weight, and determines the monitoring description parameters of each target morphological mapping indicator based on the index description detail degree.

[0053] Compared with the prior art, the beneficial effects of the present application are as follows:

[0054] Obtain the maintenance-related information of power grid equipment through the real-time status of the power grid equipment, determine the fault risk of the equipment in combination with the environmental parameters around the equipment, and conduct grading. Repair the fault according to the corresponding repair strategy. It can monitor the real-time operation status of the power grid equipment, respond to the abnormal situation of the equipment in a timely manner. At the same time, it enhances the intelligent ability of the system, quickly and accurately identifies complex fault modes, improves the reliability of the equipment and the lean level of monitoring, and ensures the operation and maintenance efficiency and cost control of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0056] Figure 1 is a schematic structural diagram of a power grid equipment fault risk monitoring and early warning system provided by an embodiment of the present invention;

[0057] Figure 2 is a schematic structural diagram of a first acquisition module provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0058] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention in conjunction with the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0059] Embodiment 1:

[0060] A power grid equipment fault risk monitoring and early warning system provided by an embodiment of the present invention, as Figure 1 shown, the system mainly includes the following modules:

[0061] The first acquisition module: Obtain the type and characteristics of the power grid equipment, and based on the type and characteristics of the power grid equipment, obtain the real-time status of the power grid equipment through the corresponding sensors;

[0062] The second acquisition module: Obtain the reliability status of the power grid equipment, and combine the real-time status to obtain the maintenance-related information of the power grid equipment by using the method of logical decision-making;

[0063] The determination module: Obtain the environmental parameters around the power grid equipment, perform maintenance on the power grid equipment in combination with the maintenance-related information, and determine the fault risk of the power grid equipment according to the maintenance results;

[0064] Level division module: divides the failure risks into levels, and issues early warnings for the failure risks of power grid equipment according to the division results;

[0065] Repair module: obtains the corresponding repair strategy according to the early warning result, and repairs the failure of power grid equipment based on the repair strategy.

[0066] In this embodiment, power grid equipment can be divided into multiple types according to its functions and uses, such as:

[0067] Transformer: A transformer is a power equipment that can change the magnitude of the AC voltage, mainly composed of an iron core, windings, etc. The characteristic of a transformer is that the transformation ratio is adjustable, and the appropriate transformation ratio can be selected according to the requirements of different occasions.

[0068] Switchgear: Switchgear mainly includes circuit breakers, disconnectors, earthing switches, etc., and is mainly used to control and protect circuits. The characteristics of switchgear are strong breaking ability and rapid action.

[0069] Protection equipment: Protection equipment mainly includes relays, overcurrent protectors, undervoltage protectors, etc., and is mainly used to detect faults and take measures to prevent the expansion of accidents. The characteristics of protection equipment are fast response speed and high sensitivity.

[0070] Measuring equipment: Measuring equipment mainly includes watt-hour meters, current transformers, voltage transformers, etc., and is mainly used to monitor and measure parameters such as current, voltage, and power in the system. The characteristics of measuring equipment are high accuracy and good reliability.

[0071] In this embodiment, for a transformer, a current sensor can be selected to measure the current; for a circuit breaker, a voltage sensor can be selected to measure the voltage.

[0072] In this embodiment, the real-time state of power grid equipment refers to the information such as the working state, working environment, and equipment performance of the equipment at the current moment.

[0073] In this embodiment, the reliability status of power grid equipment refers to the degree to which the equipment can complete the predetermined functions and indicators under normal operating conditions.

[0074] In this embodiment, the maintenance-related information includes: equipment maintenance content, maintenance type, maintenance interval, and maintenance level.

[0075] In this embodiment, the physical environment parameters around power grid equipment refer to the environmental factors that affect the performance and use safety of power grid equipment, such as:

[0076] Temperature: High temperature may cause problems such as aging of insulating materials and cable damage.

[0077] Humidity: High humidity may cause problems such as equipment corrosion and damage to electrical insulation.

[0078] Pressure: Either too high or too low pressure may lead to equipment damage or accidents.

[0079] Atmospheric conditions: Weather such as heavy fog, rain, snow, etc. may cause obstruction of vision and affect the normal operation of equipment.

[0080] In this embodiment, various faults may occur during the use of power grid equipment, resulting in equipment damage or safety accidents, such as: mechanical faults, electrical faults, thermal faults, chemical faults, material faults.

[0081] In this embodiment, the classification of fault risks includes:

[0082] Low risk level: Such risks mean that the possibility of equipment failure is relatively small under normal operating conditions. For example, new equipment, equipment that has been fully tested and verified, and equipment used strictly in accordance with operating procedures.

[0083] Medium risk level: Such risks are between low risk and high risk. Equipment may fail under certain specific conditions, such as high temperature, low temperature, humid environment, continuous high load operation, etc. For example, equipment aging, performance degradation, and failure to maintain according to regulations.

[0084] High risk level: Such risks indicate that the possibility of equipment failure is relatively large under normal operating conditions. For example, severely aged equipment, second-hand equipment put into use without being tested, improper maintenance, and improper operation.

[0085] Extra-high risk level: Such risks may lead to serious consequences, such as fire, explosion, and casualties. For example, equipment with design defects and extremely harsh operating environments.

[0086] The beneficial effects of the above technical solution are: By obtaining the maintenance-related information of power grid equipment through the real-time status of the power grid equipment, determining the fault risks of the equipment in combination with the surrounding environment parameters of the equipment, and classifying them, and repairing the faults according to the corresponding repair strategies, it is possible to monitor the real-time operating status of the power grid equipment, respond to equipment anomalies in a timely manner. At the same time, it enhances the intelligent ability of the system, quickly and accurately identifies complex fault modes, improves the reliability of the equipment and the refinement level of monitoring, and ensures the operation and maintenance efficiency and cost control of the equipment.

[0087] Embodiment 2:

[0088] Based on Embodiment 1, the first acquisition module of the embodiment of the present invention, as Figure 2 shown, includes:

[0089] The first determination unit: determines multiple pieces of information of each power grid device through the technical manual of the power grid device;

[0090] The first acquisition unit: determines the type and characteristics of the power grid device according to the multiple pieces of information, and acquires the indexes and parameters that the power grid device needs to monitor according to the type and characteristics of the power grid device;

[0091] The selection unit: selects the corresponding sensors according to the indexes and parameters to be monitored;

[0092] The second determination unit: acquires the real-time parameters of the power grid device through the sensor, analyzes them, and determines the real-time state of the power grid device according to the analysis result.

[0093] In this embodiment, the technical manual of the power grid device is a publication of a technical document that details aspects such as the product design, manufacture, installation, commissioning, maintenance, and operation of the power grid device.

[0094] In this embodiment, the multiple pieces of information include: rated voltage, rated current, and protection characteristics.

[0095] In this embodiment, the monitored indexes and parameters may include: voltage, current, load, and power.

[0096] In this embodiment, the corresponding sensors refer to, for example: for a transformer, a current sensor can be selected to measure the current; for a circuit breaker, a voltage sensor can be selected to measure the voltage.

[0097] The beneficial effects of the above technical solution are: determining the indexes and parameters to be monitored according to the type and characteristics of the power grid device, and selecting the corresponding sensors can ensure the real-time performance and accuracy of the operating state and parameters, reduce the manual maintenance and monitoring cost, and reduce the risk of equipment failure.

[0098] Embodiment 3:

[0099] Based on Embodiment 2, the second acquisition module of the embodiment of the present invention includes:

[0100] The third determination unit: acquires the service life and historical faults of the power grid device according to the database, and determines the reliability status of the power grid device according to the service life and historical faults;

[0101] The second acquisition unit: acquires the usage frequency and load condition of the power grid device according to the reliability status of the power grid device;

[0102] The fourth determination unit: determines the importance degree of each power grid device according to the usage frequency and load condition of the power grid device;

[0103] The third acquisition unit: Obtain the maintenance-related information of the grid equipment by using a logical decision-making method based on the importance degree of each grid equipment combined with the real-time state.

[0104] In this embodiment, the usage frequency of the grid equipment refers to the usage situation and usage intensity of the equipment within a certain period.

[0105] In this embodiment, the load situation of the grid equipment refers to the power demand and supply relationship of the equipment within a specific time period.

[0106] In this embodiment, determining the load situation of the grid equipment according to the reliability status of the grid equipment includes:

[0107]

[0108] Among them, is the load at the th moment and interval, is the current time point, is the time interval, which can take a constant step size (such as 1 second) here, is a device-specific constant, and are the maximum current and minimum current that the device can reach, is the current working current of the device, natural exponential function, , is the influence factor of the device reliability status, indicating the degree of influence of the device reliability status at the tth moment.

[0109] In this embodiment, the maintenance-related information includes: equipment maintenance content, maintenance type, maintenance interval period, and maintenance level.

[0110] The beneficial effects of the above technical solution are: Determine the reliability status of the grid equipment according to the usage time and historical faults of the grid equipment, so as to determine the importance degree of each equipment, and obtain the corresponding maintenance-related information based on the logical decision-making method combined with the real-time operation state, which can ensure targeted and comprehensive maintenance of the grid equipment, timely discover potential fault risks, and ensure the operation safety of the equipment.

[0111] Embodiment 4:

[0112] Based on Embodiment 3, the second acquisition unit of the embodiment of the present invention includes:

[0113] The first acquisition subunit: Obtain the data of the grid equipment reliability according to the reliability status of the grid equipment;

[0114] Evaluation sub-unit: Analyze the reliability data, obtain multiple indicators of the power grid equipment, and perform a reliability score on the power grid equipment according to the multiple indicators;

[0115] Classification sub-unit: Classify the power grid equipment according to the reliability score, and determine the start and stop time intervals of the power grid equipment, as well as the power grid load and equipment capacity according to the classification results;

[0116] First determination sub-unit: Determine the usage frequency of the power grid equipment according to the time interval, and determine the load condition of the power grid equipment according to the power grid load and equipment capacity.

[0117] In this embodiment, the reliability data includes: the reliability score of the equipment, the number of failures, and the failure duration.

[0118] In this embodiment, the indicators include: mean time between failures, failure frequency, and failure mode.

[0119] In this embodiment, the classification can be: high reliability, medium reliability, and low reliability.

[0120] In this embodiment, the power grid load refers to the total electric energy consumed by the user equipment powered by the power grid within a certain period of time.

[0121] In this embodiment, the equipment capacity refers to the maximum working ability of the equipment under specified conditions, usually measured by the processing ability per unit time.

[0122] In this embodiment, the load condition of the power grid equipment refers to the power demand and supply relationship of the equipment within a specific time period.

[0123] The beneficial effects of the above technical solutions are: determining multiple indicators of the equipment according to the reliability data of the power grid equipment, performing a reliability score on the equipment, classifying the equipment, obtaining the usage frequency and load condition of the equipment, changing the maintenance plan and replacement strategy of the equipment formulated in advance, reducing the maintenance and replacement costs caused by equipment failures, and at the same time, improving the reliability and safety of the equipment.

[0124] Embodiment 5:

[0125] Based on Embodiment 4, the determination module of the present invention embodiment includes:

[0126] Fourth acquisition unit: Obtain the ambient environment parameters of the power grid equipment through a public data source;

[0127] Judgment unit: Judge the maintenance conditions according to the ambient environment parameters, and perform maintenance on the power grid equipment according to the maintenance conditions and maintenance-related information;

[0128] Comparison unit: Compare the obtained maintenance result with the normal operation range of the equipment to obtain abnormal values;

[0129] Analysis unit: Analyze the outliers and determine the fault risk of grid equipment according to the analysis results.

[0130] In this embodiment, the public data source refers to those data resources that can be freely obtained, used, and shared by the public.

[0131] In this embodiment, the maintenance conditions usually refer to the conditions and requirements that need to be met during equipment maintenance or repair. For example, temperature-sensitive equipment is not suitable for maintenance in a high-temperature environment.

[0132] The beneficial effects of the above technical solution are as follows: Maintenance is carried out according to the ambient environment parameters and maintenance-related information of grid equipment, compared with the normal operation range of the equipment, the abnormal faults corresponding to the outliers can be obtained, the potential fault risks of the equipment can be discovered, and early warning signals can be sent in a timely manner, making the early warning more real-time and accurate. At the same time, since the early warning system and the formulation of the maintenance plan are both based on the environmental parameters and maintenance information of the equipment, waste caused by blind maintenance can be avoided.

[0133] Embodiment 6:

[0134] Based on Embodiment 5, the grade division module of the embodiment of the present invention includes:

[0135] The fifth acquisition unit: Analyze the fault risk and obtain the influencing causes of the occurrence of the fault;

[0136] The evaluation unit: Evaluate the influence degree on grid equipment according to the influencing causes, and divide the fault risk into grades according to the influence degree;

[0137] The fifth determination unit: Determine the early warning threshold for each grade based on the type, characteristics, and maintenance strategy of grid equipment;

[0138] The early warning unit: Give early warnings to the fault risks of grid equipment at different grades according to the early warning threshold.

[0139] In this embodiment, the occurrence of equipment faults is affected by various factors, such as:

[0140] Design defects: There may be problems with the design of the equipment, such as unreasonable layout, insufficient safety performance, etc., resulting in equipment failures during use.

[0141] Manufacturing defects: There may be problems with the production process or raw materials of the equipment, such as poor welding quality, part wear, etc., resulting in equipment failures during operation.

[0142] Improper use: If users do not follow the operating procedures or use the equipment beyond the rated parameters of the equipment, it may cause phenomena such as equipment overload, overvoltage, and overcurrent, which may in turn lead to failures.

[0143] Environmental factors: Harsh working environments, such as high temperature, low temperature, humidity, corrosive gases, etc., may damage the equipment and cause failures.

[0144] In this embodiment, the degree of influence on the power grid equipment refers to the degree to which the equipment can operate normally due to the influencing reasons. The equipment may be severely affected or slightly affected.

[0145] In this embodiment, the characteristics of the equipment include: stability, reliability, and economy.

[0146] In this embodiment, the maintenance strategy refers to the information related to the maintenance of the equipment, such as: the time nodes for maintaining the equipment, maintenance items, etc.

[0147] The beneficial effects of the above technical solution are: evaluating the degree of influence on the power grid equipment according to the influencing reasons of the failure, thereby classifying the failure levels, warning about the failure according to the warning threshold, and the setting of the warning threshold can be determined according to the actual operation conditions and historical data of the equipment, which can more accurately reflect the state of the equipment, thereby improving the accuracy of the warning, the operation efficiency, and the service life of the equipment.

[0148] Embodiment 7:

[0149] Based on Embodiment 6, the repair module of the present invention embodiment includes:

[0150] Query unit: Obtain warning data according to the warning result, query the corresponding repair strategy database according to the warning data, and obtain the repair strategy corresponding to the warning data;

[0151] Extraction unit: Process the queried repair strategy, extract the key information of the repair strategy, and generate a work guide corresponding to the repair strategy;

[0152] Repair unit: Repair the power grid equipment failure based on the repair strategy and the work guide.

[0153] In this embodiment, the warning data includes: warning type, warning level, and warning status.

[0154] In this embodiment, the repair strategy database is a database system for storing and managing equipment fault diagnosis and repair strategies.

[0155] In this embodiment, the key information of the repair strategy includes: repair steps, required materials, and precautions.

[0156] In this embodiment, the work guide includes: specific operations for each step, possible problems and solutions.

[0157] The beneficial effects of the above technical solution are as follows: obtaining the corresponding repair strategy according to the early warning data, extracting the key information of the repair strategy, and repairing the faults of power grid equipment can ensure the pertinence of the repair, and ensure the repair efficiency and repair results.

[0158] Embodiment 8:

[0159] Based on Embodiment 7, the first acquisition unit of the embodiment of the present invention includes:

[0160] The second acquisition subunit: determining multiple performance indicators of the power grid equipment according to the type and characteristics, and obtaining the historical performance data of the power grid equipment based on the performance indicators;

[0161] The construction subunit: constructing a three-dimensional performance parameter matrix of the power grid equipment according to the historical performance data;

[0162] The second determination subunit: determining the deterioration data items and their deterioration parameters of the power grid equipment according to the three-dimensional performance parameter matrix;

[0163] The third acquisition subunit: determining the compliance characteristics of each deterioration data item according to the deterioration parameters, and obtaining the mapping factors of each deterioration data item based on the compliance characteristics;

[0164] The first screening subunit: screening out potential dynamic factors from the mapping factors, and determining the main operation dynamic factors in the potential dynamic factors based on the working principle of the power grid equipment;

[0165] The detection subunit: detecting multiple morphological mapping indicators of the main operation dynamic factors, and determining the expression level of each morphological mapping indicator for the main operation dynamic factors according to the indicator attributes of each morphological mapping indicator;

[0166] The second screening subunit: screening out qualified target morphological mapping indicators according to the expression level, and obtaining the unit attributes of the target morphological mapping indicators;

[0167] The rating unit: determining the detection level of each target morphological mapping indicator according to the unit attributes, rating all the target morphological mapping indicators based on the detection level of each target morphological mapping indicator, and obtaining two levels;

[0168] The third determination subunit: determining the first monitoring weight of each divided target morphological mapping indicator by using the objective weighting method for the divided target morphological mapping indicators of the first level;

[0169] The fourth determination subunit: determining the second monitoring weight of each divided target morphological mapping indicator by using a combined weighting form of the subjective weighting method and the objective weighting method for the divided target morphological mapping indicators of the second level;

[0170] The fifth determination subunit: Determine the index description detail degree of each target form mapping index based on the first monitoring weight and the second monitoring weight, and determine the monitoring description parameter of each target form mapping index based on the index description detail degree.

[0171] In this embodiment, power grid equipment usually has multiple important performance indicators, including:

[0172] Electrical performance: Electrical performance mainly includes the performance in aspects such as voltage, current, power factor, and frequency.

[0173] Mechanical performance: This refers to the mechanical performance shown by the equipment during use, such as durability, stiffness, vibration resistance, etc.

[0174] Reliable performance: The reliable degree of the equipment under normal and abnormal conditions, evaluated from multiple angles such as the working state of the equipment, the frequency of faults occurring, and the fault recovery ability.

[0175] In this embodiment, the historical performance data of power grid equipment refers to various data generated during the operation of power grid equipment in the past period of time, such as:

[0176] Electrical performance data: Such as voltage, current, power factor, frequency, etc.

[0177] Mechanical performance data: Such as vibration, noise, temperature, etc.

[0178] Environmental performance data: Such as humidity, temperature, air pressure, etc.

[0179] Safety performance data: Such as the number of faults, fault types, fault duration, etc.

[0180] In this embodiment, the three-dimensional performance parameter matrix is a mathematical tool for describing the performance of power grid equipment, which includes various performance parameters of the equipment and the relationships between these parameters. The three-dimensional performance parameter matrix mainly includes three dimensions: the equipment dimension, the parameter dimension, and the evaluation dimension. In the matrix, each row represents a piece of equipment, including the name of the equipment (Equipment A, Equipment B, Equipment C), a specific parameter value (such as voltage, current, power), and the index in the corresponding evaluation dimension (such as meeting the standard requirements). For example, if a parameter value is 90V, which exceeds the allowable deviation range but is within the allowable range, it can be recorded as: Equipment A, voltage 90V, deviation range within the allowable range.

[0181] In this embodiment, the power grid equipment deterioration data item refers to the key information that can reflect the change of the equipment state, such as: vibration data, temperature data, pressure data.

[0182] In this embodiment, the degradation parameter is a quantitative index used to evaluate the degree of degradation of a device, reflecting the degree of degradation that occurs to the device over a certain period of time, and can provide a basis for judging the remaining service life of the device. For example: vibration frequency, vibration amplitude, temperature change.

[0183] In this embodiment, the compliance characteristics of the degradation data item refer to that when the degradation data of the device meets certain standards during use, the device can be considered to be in a good state. For example: stable vibration frequency, normal vibration amplitude, stable temperature change.

[0184] In this embodiment, in the power equipment condition monitoring and early warning system, the mapping factors of the data item mainly refer to the factors that affect the evaluation result of the equipment condition in various links such as physical quantity conversion, signal processing, and equipment behavior analysis. For example: conversion factor, threshold setting, environment, etc.

[0185] In this embodiment, the potential dynamic factors refer to various internal and external factors that may affect the real-time change of the equipment condition in the equipment condition monitoring and early warning. For example:

[0186] External environmental factors: such as weather changes, natural disasters, social activities, etc.

[0187] Internal factors: such as material fatigue, aging, design defects of the equipment itself, etc.

[0188] Operation factors: such as operator errors, negligence, illegal operations, etc.

[0189] In this embodiment, the operation dynamic factors refer to various factors that affect the operation efficiency and effect of the equipment under the constraints of a certain specific environment and other conditions. For example, technical factors.

[0190] In this embodiment, the expression level of the operation dynamic factors mainly refers to the accuracy of the monitoring data and the intelligence of the data analysis.

[0191] In this embodiment, for example, if the main operation dynamic factor is the environment, then its morphological mapping index is a quantitative index that measures the relationship between the equipment and the environment, and can describe the spatial relationship and distribution characteristics between the equipment and the environment. For example: area ratio index, boundary length ratio index, shape complexity index.

[0192] In this embodiment, the unit attribute of the morphological mapping index depends on the specific index used. For example: perimeter, area, volume, density.

[0193] In this embodiment, the detection level refers to the balance between the different precisions and reliabilities of the equipment detection tasks, and the detection level involves different levels from low-level detection (such as simple appearance detection, shape detection) to high-level detection (such as voltage detection, power detection, etc.).

[0194] In this embodiment, the objective weighting method is a method based on objective data and indicators, used for relative evaluation and ranking of different objects. For example, the correlation coefficient method is based on the correlation between each feature and the target variable, assigns a weight to each target form mapping indicator, and uses the weighted arithmetic mean as the final evaluation indicator. The larger the absolute value of the correlation coefficient, the closer the relationship between the feature and the target variable.

[0195] In this embodiment, the monitoring weight refers to the importance of monitoring each form mapping indicator. The more important the indicator, the greater the monitoring weight.

[0196] In this embodiment, the detail degree of the indicator description refers to whether the description of a specific indicator is detailed and clear.

[0197] In this embodiment, the monitoring description parameters refer to various parameters that need to be concerned during a certain monitoring, such as: monitoring purpose, type of monitoring parameters, monitoring location.

[0198] The beneficial effects of the above technical solution are as follows: By analyzing the historical performance data of power grid equipment, constructing a three-dimensional performance parameter matrix, determining the deterioration data items and deterioration parameters based on this matrix, screening out the main operation dynamic factors and analyzing their form mapping indicators, determining the expression levels of each indicator accordingly, then selecting qualified indicators and obtaining their unit attributes, rating them according to the detection levels of each indicator, and determining the monitoring description parameters for them in an objective and subjective combination manner, it is possible to quickly and accurately obtain the indicators and parameters that need to be monitored. At the same time, the accuracy of the indicators and parameters is ensured, laying a foundation for subsequent selection of sensors and ensuring the real-time acquisition of the operating state.

[0199] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course also by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0200] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A power grid equipment failure risk monitoring and early warning system, characterized in that: include: The first acquisition module is used to acquire the type and characteristics of the power grid equipment, and acquire the real-time status of the power grid equipment based on the corresponding sensor according to the type and characteristics of the power grid equipment; The second acquisition module: obtains the reliability status of power grid equipment, and uses logical decision-making methods in combination with real-time status to obtain maintenance-related information of power grid equipment; Determination module: obtains the surrounding environment parameters of the power grid equipment, performs maintenance on the power grid equipment in combination with maintenance-related information, and determines the failure risk of the power grid equipment based on the maintenance results; Classification module: classifies the fault risks into different levels, and issues early warnings for the fault risks of power grid equipment according to the classification results; Repair module: obtains the corresponding repair strategy according to the early warning results, and repairs the power grid equipment failure based on the repair strategy; Wherein, the first acquisition module includes: A first determining unit: determining multiple information of each power grid device through a technical manual of the power grid device; A first acquisition unit: determining the type and characteristics of the power grid equipment according to the plurality of information, and acquiring the indicators and parameters that need to be monitored for the power grid equipment according to the type and characteristics of the power grid equipment; Selection unit: selects corresponding sensors according to the indicators and parameters to be monitored; A second determining unit: acquiring real-time parameters of the power grid equipment through the sensor, analyzing the parameters, and determining the real-time status of the power grid equipment according to the analysis results; Wherein, the first acquisition unit includes: The second acquisition subunit determines a plurality of performance indicators of the power grid equipment according to the type and characteristics, and acquires historical performance data of the power grid equipment based on the performance indicators; Construction subunit: construct a three-dimensional performance parameter matrix of power grid equipment based on historical performance data; The second determination subunit is configured to determine the degradation data items and degradation parameters of the power grid equipment according to the three-dimensional performance parameter matrix; The third acquisition subunit: determines the standard-compliant feature of each degraded data item according to the degradation parameter, and acquires the mapping factor of each degraded data item based on the standard-compliant feature; The first screening sub-unit: screens out potential dynamic factors from the mapping factors, and determines the main operational dynamic factors from the potential dynamic factors based on the working principle of the power grid equipment; Detection subunit: detect multiple morphological mapping indicators of the main operational dynamic factors, and determine the expression level of the morphological mapping indicator for the main operational dynamic factors according to the indicator attribute of each morphological mapping indicator, wherein the expression level refers to the accuracy of the monitoring data and the intelligence of the data analysis; The second screening subunit: screening out qualified target morphological mapping indicators according to the expression level, and obtaining unit attributes of the target morphological mapping indicators; Rating unit: determining the detection level of each target morphology mapping indicator according to the unit attribute, rating all target morphology mapping indicators based on the detection level of each target morphology mapping indicator, and obtaining two levels; The third determination subunit: performing an objective weighting method on the first-level segmentation target morphology mapping indicator to determine a first monitoring weight of each segmentation target morphology mapping indicator; Fourth determination subunit: performing a combination of subjective weighting method and objective weighting method on the second sector's division target morphology mapping indicator to determine a second monitoring weight of each division target morphology mapping indicator; The fifth determining subunit determines the indicator description detail of each target morphology mapping indicator based on the first monitoring weight and the second monitoring weight, and determines the monitoring description parameters of each target morphology mapping indicator based on the indicator description detail.

2. The power grid equipment failure risk monitoring and early warning system according to claim 1 is characterized in that: The second acquisition module includes: A third determination unit: obtaining the service life and historical failures of the power grid equipment according to the database, and determining the reliability status of the power grid equipment according to the service life and historical failures; A second acquisition unit: acquiring the usage frequency and load status of the power grid equipment according to the reliability status of the power grid equipment; A fourth determining unit: determining the importance of each power grid device according to the usage frequency and load condition of the power grid device; The third acquisition unit: obtains maintenance-related information of power grid equipment by using a logical decision-making method based on the importance of each power grid equipment and its real-time status.

3. The power grid equipment failure risk monitoring and early warning system according to claim 2 is characterized in that: The second acquisition unit includes: A first acquisition subunit: acquiring data on the reliability of the power grid equipment according to the reliability status of the power grid equipment; Scoring subunit: analyzing the reliability data, obtaining multiple indicators of power grid equipment, and scoring the reliability of the power grid equipment according to the multiple indicators; Classification subunit: classify the grid equipment according to the reliability score, and determine the time interval for activation and deactivation of the grid equipment, as well as the grid load and equipment capacity according to the classification results; The first determination subunit determines the use frequency of the power grid equipment according to the time interval, and determines the load condition of the power grid equipment according to the power grid load and the equipment capacity.

4. The power grid equipment failure risk monitoring and early warning system according to claim 1 is characterized in that: Identify modules, including: Fourth acquisition unit: acquiring surrounding environment parameters of power grid equipment through a public data source; Judgment unit: judges the maintenance conditions according to the surrounding environment parameters, and performs maintenance on the power grid equipment according to the maintenance conditions and maintenance related information; Comparison unit: compares the obtained maintenance results with the normal operating range of the equipment to obtain abnormal values; Analysis unit: Analyze the abnormal values ​​and determine the failure risk of the power grid equipment based on the analysis results.

5. The power grid equipment failure risk monitoring and early warning system according to claim 1 is characterized in that: The level classification module includes: A fifth acquisition unit: analyzing the failure risk to acquire the cause of the failure; Evaluation unit: evaluates the degree of influence on the power grid equipment according to the influence cause, and classifies the fault risk according to the degree of influence; The fifth determination unit determines the warning threshold of each level based on the type, characteristics and maintenance strategy of the power grid equipment; Early warning unit: Issue early warnings for different levels of power grid equipment failure risks based on early warning thresholds.

6. The power grid equipment failure risk monitoring and early warning system according to claim 1 is characterized in that: Repair modules, including: Query unit: obtains warning data according to the warning result, queries the corresponding repair strategy database according to the warning data, and obtains the repair strategy corresponding to the warning data; Extraction unit: processes the queried repair strategy, extracts key information of the repair strategy, and generates a work guide corresponding to the repair strategy; Repair unit: Repair power grid equipment failures based on repair strategies and work guidelines.

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