CN118396215A - Evaluation system of intelligent alarm of transformer substation monitoring system - Google Patents
Evaluation system of intelligent alarm of transformer substation monitoring system Download PDFInfo
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Abstract
本发明公开了一种变电站监控系统智能告警的评估系统，涉及电力监测技术领域，包括要素抓取模块、回归分析模块、阈值比对模块、预警通报模块，采集变电站监控系统智能告警的评估系统的感应精度信息和评估信任度信息，并传送至回归分析模块对感应精度信息和评估信任度信息进行综合分析，建立分析模型，运用逻辑回归方法计算置信偏差指数，将计算所得的置信偏差指数与预设置信偏差指数进行比对，对系统检测状态可信性进行信号分类，根据系统的信号类型进行预警处理，本发明能够对评估系统运行状态进行监测，当运行状态不满足可信性要求时，发出预警提示，提醒工作人员及时介入处理。
The invention discloses an evaluation system for intelligent alarm of a substation monitoring system, which relates to the technical field of electric power monitoring, and comprises an element capture module, a regression analysis module, a threshold comparison module, and an early warning notification module. The system collects sensing accuracy information and evaluation trust information of the evaluation system for intelligent alarm of the substation monitoring system, and transmits the information to the regression analysis module for comprehensive analysis of the sensing accuracy information and the evaluation trust information, establishes an analysis model, calculates a confidence deviation index by a logistic regression method, compares the calculated confidence deviation index with a preset confidence deviation index, performs signal classification on the credibility of the system detection state, and performs early warning processing according to the signal type of the system. The invention can monitor the operating state of the evaluation system, and when the operating state does not meet the credibility requirement, issues an early warning prompt to remind the staff to intervene in the processing in time.
Description
Technical Field
The invention relates to the technical field of power monitoring, in particular to an intelligent alarm evaluation system of a transformer substation monitoring system.
Background
The system for evaluating intelligent alarms of a substation monitoring system is a system for evaluating intelligent alarm functions of substation monitoring devices in a power system, in which a substation plays a key role in converting electric energy of a high-voltage transmission line into low-voltage electric energy suitable for distribution, and in order to ensure stable and reliable operation of the power system, the substation is generally equipped with various monitoring devices for monitoring states and performances of the power devices in real time.
The intelligent alarm system can monitor various parameters of substation equipment, such as current, voltage, temperature and the like in real time by using a sensor technology and a data analysis algorithm, when abnormal or exceeding a preset threshold value is monitored, the system can generate an alarm and inform operation and maintenance personnel to take corresponding measures so as to prevent potential faults or accidents, the judgment of the alarm system depends on the preset state classification threshold value, the existing judgment method carries out evaluation and judgment according to the equipment operation index of the substation monitoring system, the input model does not comprise the detection effectiveness index of the evaluation system, the front fault factor and the rear fault judgment result cannot be combined, the comprehensiveness of evaluation logic is difficult to comprehensively consider, and the situation that the effective support degree is difficult to improve is caused.
In order to solve the above-mentioned defect, a technical scheme is proposed.
Disclosure of Invention
The invention aims to provide an evaluation system for intelligent alarm of a transformer substation monitoring system, which aims to solve the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions: the evaluation system of the intelligent alarm of the transformer substation monitoring system is characterized by comprising an element grabbing module, a regression analysis module, a threshold value comparison module and an early warning notification module;
the element grabbing module is used for collecting induction precision information and evaluation trust information of an evaluation system of intelligent alarm of the substation monitoring system and transmitting the induction precision information and the evaluation trust information to the regression analysis module;
The regression analysis module is used for comprehensively analyzing the induction precision information and the evaluation trust information, establishing an analysis model, and calculating the confidence deviation index of the evaluation system of the intelligent alarm of the substation monitoring system by using a logistic regression method;
the threshold value comparison module is used for comparing the calculated confidence deviation index with a preset confidence deviation index, and carrying out signal classification on the detection state reliability of the evaluation system of the intelligent alarm of the transformer substation monitoring system according to the comparison result;
The early warning notification module is used for carrying out early warning processing according to the signal type of the evaluation system of the intelligent warning of the transformer substation monitoring system.
Preferably, the sensing precision information comprises a scanning uploading fluctuation coefficient and a vibration updating period floating coefficient, and the trust degree information is estimated as an alarm response estimation coefficient.
Preferably, the calculation method of the scanning uploading fluctuation coefficient comprises the following steps:
S101, acquiring the scanning uploading frequency of the intelligent alarm of the substation monitoring system, wherein the scanning uploading frequency of the pressure sensor is operated by the intelligent alarm evaluation system of the substation monitoring system in the T time, calibrating the monitoring frequency of the scanning uploading frequency of the pressure sensor operated by the intelligent alarm evaluation system of the substation monitoring system in the T time as Tr, and r is the number of the scanning uploading frequency of the pressure sensor operated by the intelligent alarm evaluation system of the substation monitoring system in the T time, wherein the number of the scanning uploading frequency of the pressure sensor is calculated by the intelligent alarm evaluation system of the substation monitoring system in the T time, and Wherein e is a positive integer;
s102, acquiring a minimum scanning uploading frequency value of the intelligent alarm of the substation monitoring system, wherein the minimum scanning uploading frequency value of the pressure sensor is operated by the intelligent alarm evaluation system of the substation monitoring system in the T time, and calibrating the minimum scanning uploading frequency value of the pressure sensor by the intelligent alarm evaluation system of the substation monitoring system in the T time as La;
s103, the pair meets The method comprises the steps that scanning uploading frequency of a pressure sensor operated by an evaluation system of intelligent warning of a transformer substation monitoring system in T time is extracted and integrated into a low-frequency data set, the low-frequency data set is numbered to be Pl according to a time sequence of the scanning uploading frequency of the pressure sensor, which is acquired by the evaluation system of intelligent warning of the transformer substation monitoring system in T time, l is the data number, andWherein j is a positive integer;
S104, calculating the expression of the scanning uploading fluctuation coefficient as follows 。
Preferably, the method for calculating the vibration update period floating coefficient comprises the following steps:
S201, acquiring a reasonable error range of a vibration monitoring period of an evaluation system of the intelligent alarm of the transformer substation monitoring system, and calibrating the reasonable error range of the vibration monitoring period of the evaluation system of the intelligent alarm of the transformer substation monitoring system to be Vi1-Vi2;
s202, acquiring a vibration monitoring period of an evaluation system of intelligent alarm of a substation monitoring system, and calibrating data of the vibration monitoring period of the evaluation system of intelligent alarm of the substation monitoring system as Vb;
S203, integrating a plurality of vibration monitoring period data of the transformer substation monitoring system intelligent alarm evaluation system in the T time into a data set, and marking the serial numbers of the vibration monitoring water level data with b, namely Wherein g is a positive integer;
s204, calculating the standard deviation of the vibration monitoring period data set, and then obtaining the standard deviation In which, in the process,For the average value of the vibration monitoring period data set, the calculation expression is；
S205, calculating the expression of the vibration update period floating coefficient as。
Preferably, the calculation method of the alarm response evaluation coefficient comprises the following steps:
s301, setting a preset reference value for a comprehensive evaluation index of alarm accuracy of an evaluation system of intelligent alarm of a transformer substation monitoring system in T time, and calibrating the preset reference value of the comprehensive evaluation index to be Bu, wherein Bu is larger than 1;
the preset reference value of the comprehensive evaluation index ranges from 0 to 1, and indexes of the matching accuracy P and the recall R can be comprehensively considered;
S302, acquiring comprehensive evaluation indexes of the intelligent alarm evaluation system of the substation monitoring system in different time periods within the T time, calibrating the comprehensive evaluation indexes to be Ax, wherein x represents the number of the comprehensive evaluation indexes of the intelligent alarm evaluation system of the substation monitoring system of the game background user in different time periods within the T time, and P is a positive integer;
The expression of the comprehensive evaluation index calculation is that In the formula, P represents the matching accuracy, the judging accuracy refers to the proportion of the abnormal state in the evaluation system of the intelligent alarm of the substation monitoring system, which is judged to be in the abnormal state, and the calculating method comprises the following steps: matching accuracy = number of abnormal states correctly matched/number of all abnormal states determined, R represents recall, which refers to the ratio between the number of abnormal states correctly matched by the evaluation system of the intelligent alarm of the substation monitoring system and the number of all actual abnormal states, and the calculation method is as follows: recall = number of abnormal states correctly matched/number of all actual abnormal states;
the number of the abnormal states is the number of the abnormal states which are judged by the intelligent alarms of the substation monitoring system in a certain time range, wherein the real abnormal states and the misjudged normal states are included, the detection states are generally classified and marked by the intelligent alarms of the substation monitoring system, or the abnormal judgment conditions of transactions are recorded in a log, and the abnormal judgment conditions can be obtained by counting the number of the abnormal states marked by the intelligent alarms of the substation monitoring system;
The number of all actual abnormal states refers to the number of all abnormal states existing under the actual condition, and the actual abnormal states are possibly caused by detection and judgment errors, so that an evaluation system of intelligent alarm of a transformer substation monitoring system needs to interact with a power terminal server or a database to acquire the number of the actual abnormal states;
s303, calculating an expression of an alarm response evaluation coefficient as follows 。
Preferably, the method for calculating the confidence deviation index of the evaluation system of the intelligent alarm of the substation monitoring system comprises the following steps:
The regression analysis module performs comprehensive analysis according to the scanning uploading fluctuation coefficient, the vibration updating period floating coefficient and the alarm response evaluation coefficient, establishes a management model, calculates the confidence deviation index of the intelligent alarm evaluation system of the transformer substation monitoring system, and calculates the confidence deviation index as follows In which, in the process,Scanning and uploading the scaling factors of the fluctuation coefficient, the vibration update period floating coefficient and the alarm response evaluation coefficient, andAre all greater than 0.
Preferably, the logic for classifying the signals of the reliability of the detection state of the evaluation system of the intelligent alarm of the substation monitoring system is as follows:
Comparing the calculated confidence deviation index of the intelligent alarm evaluation system of the transformer substation monitoring system with a preset confidence deviation index threshold, generating a sensitive signal if the calculated confidence deviation index is greater than or equal to the preset confidence deviation index, and generating a steady-state signal if the calculated confidence deviation index is less than the preset confidence deviation index.
Preferably, the logic for performing early warning processing on the evaluation system of the intelligent alarm of the transformer substation monitoring system is as follows:
The early warning notification module performs processing strategy analysis according to the sensitive signals generated by the threshold comparison module, after receiving the sensitive signals generated by the threshold comparison module, the early warning notification module integrates and generates a data set according to a plurality of continuous confidence deviation index data of an evaluation system of intelligent warning of a transformer substation monitoring system within T time after the sensitive signals are generated, and the confidence deviation index in the data set is calibrated to be Rv, wherein v is the confidence deviation index number, namely Wherein x is a positive integer;
Calculating standard deviation of a plurality of confidence deviation indexes in a data set, calibrating the standard deviation of the confidence deviation indexes as So, comparing the standard deviation of the confidence deviation indexes with a preset standard deviation threshold Do of the confidence deviation indexes, and performing early warning processing according to comparison results, wherein the processing logic is as follows:
If So is greater than or equal to Do, marking an evaluation system for intelligent alarm of a substation monitoring system as a high risk level, prompting staff that the evaluation system for intelligent alarm of the substation monitoring system has an unreliable risk hidden danger, and detecting and maintaining are needed;
if So is smaller than Do, marking the evaluation system for intelligent alarm of the substation monitoring system as a low risk level, prompting staff that the evaluation system for intelligent alarm of the substation monitoring system has low risk hidden danger, and no detection and maintenance are needed.
In the technical scheme, the invention has the technical effects and advantages that:
According to the invention, through detecting the confidence deviation index of the intelligent alarm evaluation system of the transformer substation monitoring system, when the occurrence of abnormal data processing reliability is found, the subsequent operation state of the intelligent alarm evaluation system of the transformer substation monitoring system is comprehensively analyzed, the abnormal hidden danger is judged, and an early warning prompt is sent, so that a worker can be effectively assisted to acquire the potential hidden danger state, the potential hidden danger is checked and solved in advance, the operation effectiveness of the evaluation system is prevented from entering the invisible failure state, the workload of the worker is reduced, and the management efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a block diagram of a system according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, the invention relates to an evaluation system for intelligent alarm of a transformer substation monitoring system, which comprises an element grabbing module, a regression analysis module, a threshold value comparison module and an early warning notification module;
the element grabbing module is used for collecting induction precision information and evaluation trust information of an evaluation system of intelligent alarm of the substation monitoring system and transmitting the induction precision information and the evaluation trust information to the regression analysis module;
The regression analysis module is used for comprehensively analyzing the induction precision information and the evaluation trust information, establishing an analysis model, and calculating the confidence deviation index of the evaluation system of the intelligent alarm of the substation monitoring system by using a logistic regression method;
the threshold value comparison module is used for comparing the calculated confidence deviation index with a preset confidence deviation index, and carrying out signal classification on the detection state reliability of the evaluation system of the intelligent alarm of the transformer substation monitoring system according to the comparison result;
The early warning notification module is used for carrying out early warning processing according to the signal type of the evaluation system of the intelligent warning of the transformer substation monitoring system.
The sensing precision information comprises a scanning uploading fluctuation coefficient and a vibration updating period floating coefficient, and the trust degree information is estimated as an alarm response estimating coefficient.
The intelligent alarm evaluation system of the transformer substation monitoring system is an intelligent system for monitoring and managing the operation state of a power substation, the power substation is an important component part in a power system and is used for transforming, distributing and transmitting the electric energy of a high-voltage transmission line to a user or other power grids, and the purpose of the monitoring system is to ensure the stable operation of the power system, improve the operation efficiency, and timely discover and process potential problems so as to reduce the possibility of power failure and faults.
The application monitors the pressure of the insulating oil of the transformer through a pressure sensor, and the specific action of the insulating oil in the transformer is as follows:
Insulation: the insulating oil is mainly used for providing electrical insulation between windings of the transformer and other electrical components, has high electrical insulation performance, can prevent current from generating short circuit between windings or between the windings and the ground, and can ensure safe transmission of electric energy and normal operation of the transformer;
And (3) cooling: when current passes through the windings of the transformer, certain heat is generated, and insulating oil has excellent thermal conductivity and can absorb and transfer the heat, and by flowing around the windings, the insulating oil cools the transformer, so that the equipment is ensured to work in a proper temperature range, the windings are prevented from being overheated, and the transformer is protected from damage;
Protection: the insulating oil also plays a role in protecting the internal components of the transformer, can prevent oxidation and corrosion of windings and other metal components and the influence of air and humid environment, and helps to prolong the service life of the transformer by keeping the internal components clean and dry.
When the frequency fluctuation of the pressure sensor for monitoring the insulation oil pressure of the transformer is too large, the following adverse effects may be generated on an evaluation system for intelligent alarm of a transformer substation monitoring system:
false or missing report: frequent pressure fluctuations may lead to false alarms or false alarms, i.e., the system may incorrectly generate alarms, or fail to generate alarms when there is really a problem, which may affect the accuracy of the system, making it difficult to correctly identify potential faults or anomalies;
Alarm fatigue: too frequent alarms may cause the operator to lose confidence in the alarms of the system, making them tired in the alarms, and when a problem is actually occurring, the operator may ignore the alarms, thereby delaying the time to take necessary measures;
System performance decreases: excessive frequency fluctuation can negatively affect the overall performance of the intelligent alarm evaluation system, making it difficult to operate stably, which can lead to performance degradation of the system, affecting timely and accurate identification and response of the real problem;
The energy consumption is increased: frequent alarms may cause the system to perform unnecessary computations and processing, increasing the energy consumption of the system, which may not only affect the reliability of the system, but may also increase the cost of operation and maintenance.
The reliability evaluation is carried out on the monitoring state of the pressure sensor through the scanning uploading frequency of the monitoring pressure sensor, the reference index is the scanning uploading fluctuation coefficient, and the calculation method is as follows:
S101, acquiring the scanning uploading frequency of the intelligent alarm of the substation monitoring system, wherein the scanning uploading frequency of the pressure sensor is operated by the intelligent alarm evaluation system of the substation monitoring system in the T time, calibrating the monitoring frequency of the scanning uploading frequency of the pressure sensor operated by the intelligent alarm evaluation system of the substation monitoring system in the T time as Tr, and r is the number of the scanning uploading frequency of the pressure sensor operated by the intelligent alarm evaluation system of the substation monitoring system in the T time, wherein the number of the scanning uploading frequency of the pressure sensor is calculated by the intelligent alarm evaluation system of the substation monitoring system in the T time, and Wherein e is a positive integer;
It should be noted that, the scanning period of the pressure sensor in the evaluation system of the intelligent alarm of the substation monitoring system depends on the type, capacity, design specification and operation condition of the transformer, and the scanning uploading frequency of the insulating oil pressure of different transformers is different;
s102, acquiring a minimum scanning uploading frequency value of the intelligent alarm of the substation monitoring system, wherein the minimum scanning uploading frequency value of the pressure sensor is operated by the intelligent alarm evaluation system of the substation monitoring system in the T time, and calibrating the minimum scanning uploading frequency value of the pressure sensor by the intelligent alarm evaluation system of the substation monitoring system in the T time as La;
It should be noted that, the single-board machine monitoring tool assembly can be used for carrying out state analysis and monitoring on the evaluation system of the intelligent alarm of the substation monitoring system, the common monitoring tool assembly comprises HWiNFO, nagios, zabbix and the like, and the multi-dimensional data model can be used or the single-board machine operation data can be defined with labels through the self-defined monitoring options, and the state data can be recorded and stored through the time sequence;
s103, the pair meets The method comprises the steps that scanning uploading frequency of a pressure sensor operated by an evaluation system of intelligent warning of a transformer substation monitoring system in T time is extracted and integrated into a low-frequency data set, the low-frequency data set is numbered to be Pl according to a time sequence of the scanning uploading frequency of the pressure sensor, which is acquired by the evaluation system of intelligent warning of the transformer substation monitoring system in T time, l is the data number, andWherein j is a positive integer;
S104, calculating the expression of the scanning uploading fluctuation coefficient as follows ；
The expression of the scanning uploading fluctuation coefficient shows that the larger the scanning uploading fluctuation coefficient generated by the evaluation system of the intelligent alarm of the transformer substation monitoring system in the T time is, the worse the reliability of the operation of the evaluation system of the intelligent alarm of the transformer substation monitoring system is, otherwise, the smaller the scanning uploading fluctuation coefficient generated by the evaluation system of the intelligent alarm of the transformer substation monitoring system in the T time is, the better the reliability of the operation of the evaluation system of the intelligent alarm of the transformer substation monitoring system is.
The intelligent alarm evaluation system of the transformer substation monitoring system monitors vibration of mechanical equipment in a power station, particularly equipment with more moving mechanical parts, such as a motor, which is widely applied in an electric power system, and the vibration monitoring of a rotor and a bearing of the motor is helpful for detecting potential mechanical problems such as unbalance, abrasion, bearing faults and the like;
In the present application, the vibration refers to an electromechanical device including a motor, including, but not limited to, a transformer, a frequency converter, a switching device, a compressor, a pump, and the like.
If the vibration detection period of the mechanical power equipment is too long, the reliability of the evaluation system for intelligent alarm of the substation monitoring system is affected as follows:
Failure to detect timely: long period vibration monitoring means that vibration anomalies of the equipment can only be detected for longer time intervals, during which time potential faults may have developed into more serious problems, resulting in reduced performance of the equipment or even faults;
Preventive maintenance cannot be performed: too long vibration monitoring period may mean that the best opportunity to perform preventive maintenance is missed, and by finding and solving potential problems in time, the occurrence of faults can be avoided, and the reliability and the service life of equipment can be improved;
Increasing maintenance and repair costs: if the vibration monitoring period is too long, once a fault occurs, emergency maintenance or repair may be needed, the maintenance is often more expensive than preventive protection, and meanwhile, the equipment downtime may be increased, so that the production and service continuity is affected;
The service life of the equipment is shortened: failure to detect and resolve mechanical faults in time may lead to reduced equipment life, vibration anomalies may accelerate wear and damage to mechanical components, and long-term monitoring may not allow for timely treatment of these problems;
security risk increases: if abnormality of vibration of the equipment cannot be detected in time, instability of the equipment can be increased, and risk of accidents is increased, so that safety is affected.
And the vibration monitoring effectiveness of the intelligent alarm evaluation system of the transformer substation monitoring system is evaluated by calculating the vibration updating period floating coefficient, wherein the calculation process is as follows:
S201, acquiring a reasonable error range of a vibration monitoring period of an evaluation system of the intelligent alarm of the transformer substation monitoring system, and calibrating the reasonable error range of the vibration monitoring period of the evaluation system of the intelligent alarm of the transformer substation monitoring system to be Vi1-Vi2;
the method is characterized in that the reasonable error range of the effective vibration monitoring period is checked through a comparison test of the running state of the power equipment and the data of the vibration monitoring device, the reasonable error range of the effective vibration monitoring period is not influenced by the normal running of the power equipment, and the test setting is carried out by a person skilled in the art according to the actual situation;
s202, acquiring a vibration monitoring period of an evaluation system of intelligent alarm of a substation monitoring system, and calibrating data of the vibration monitoring period of the evaluation system of intelligent alarm of the substation monitoring system as Vb;
S203, integrating a plurality of vibration monitoring period data of the transformer substation monitoring system intelligent alarm evaluation system in the T time into a data set, and marking the serial numbers of the vibration monitoring water level data with b, namely Wherein g is a positive integer;
s204, calculating the standard deviation of the vibration monitoring period data set, and then obtaining the standard deviation In which, in the process,For the average value of the vibration monitoring period data set, the calculation expression is；
S205, calculating the expression of the vibration update period floating coefficient as；
According to the calculation expression of the vibration update period floating coefficient, the greater the vibration update period floating coefficient of the intelligent alarm evaluation system of the transformer substation monitoring system is, the worse the reliability of the intelligent alarm evaluation system of the transformer substation monitoring system is, otherwise, the smaller the vibration update period floating coefficient of the intelligent alarm evaluation system of the transformer substation monitoring system is, the better the reliability of the intelligent alarm evaluation system of the transformer substation monitoring system is;
the alarm accuracy of the intelligent alarm evaluation system of the transformer substation monitoring system is analyzed through an alarm response evaluation coefficient, and the specific calculation process is as follows:
s301, setting a preset reference value for a comprehensive evaluation index of alarm accuracy of an evaluation system of intelligent alarm of a transformer substation monitoring system in T time, and calibrating the preset reference value of the comprehensive evaluation index to be Bu, wherein Bu is larger than 1;
It should be noted that, the preset reference value of the comprehensive evaluation index is a quantized specific reference value, and is not specifically limited herein, bu is a value greater than 1, the comprehensive evaluation index, that is, the F value, ranges from 0 to 1, and indexes of the matching accuracy P and the recall R can be comprehensively considered, so that the evaluation system for measuring the intelligent alarm of the substation monitoring system can accurately identify the abnormal state, the evaluation system for the intelligent alarm of the substation monitoring system can avoid misjudging the normal state as the abnormal state, the detection processing of the evaluation system for the intelligent alarm of the substation monitoring system on the abnormal state can be more accurately performed, the detection effect can be improved, the high F value means that the recall of the evaluation system for the intelligent alarm of the substation monitoring system on the abnormal state is higher, and error leakage errors can be effectively reduced, so as to extract the real abnormal state;
S302, acquiring comprehensive evaluation indexes of the intelligent alarm evaluation system of the substation monitoring system in different time periods within the T time, calibrating the comprehensive evaluation indexes to be Ax, wherein x represents the number of the comprehensive evaluation indexes of the intelligent alarm evaluation system of the substation monitoring system of the game background user in different time periods within the T time, and P is a positive integer;
The expression of the comprehensive evaluation index calculation is that In the formula, P represents the matching accuracy, the judging accuracy refers to the proportion of the abnormal state in the evaluation system of the intelligent alarm of the substation monitoring system, which is judged to be in the abnormal state, and the calculating method comprises the following steps: matching accuracy = number of abnormal states correctly matched/number of all abnormal states determined, R represents recall, which refers to the ratio between the number of abnormal states correctly matched by the evaluation system of the intelligent alarm of the substation monitoring system and the number of all actual abnormal states, and the calculation method is as follows: recall = number of abnormal states correctly matched/number of all actual abnormal states;
It should be noted that, the number of abnormal states that are correctly matched refers to the number of abnormal states that are correctly identified and judged by the evaluation system of the intelligent alarm of the substation monitoring system, and the evaluation system of the intelligent alarm of the substation monitoring system marks the detected abnormal states or puts the detected abnormal states into a database of abnormal state records, and the number of abnormal states that are correctly judged can be obtained by inquiring the number of abnormal state records;
the number of the abnormal states is the number of the abnormal states which are judged by the intelligent alarms of the substation monitoring system in a certain time range, wherein the real abnormal states and the misjudged normal states are included, the detection states are generally classified and marked by the intelligent alarms of the substation monitoring system, or the abnormal judgment conditions of transactions are recorded in a log, and the abnormal judgment conditions can be obtained by counting the number of the abnormal states marked by the intelligent alarms of the substation monitoring system;
The number of all actual abnormal states refers to the number of all abnormal states existing under the actual condition, and the actual abnormal states are possibly caused by detection and judgment errors, so that an evaluation system of intelligent alarm of a transformer substation monitoring system needs to interact with a power terminal server or a database to acquire the number of the actual abnormal states;
s303, calculating an expression of an alarm response evaluation coefficient as follows ；
According to the calculation expression of the alarm response evaluation coefficient, the greater the alarm response evaluation coefficient of the intelligent alarm evaluation system of the transformer substation monitoring system is, the worse the reliability of the intelligent alarm evaluation system of the transformer substation monitoring system is, otherwise, the smaller the alarm response evaluation coefficient of the intelligent alarm evaluation system of the transformer substation monitoring system is, the better the operation reliability of the intelligent alarm evaluation system of the transformer substation monitoring system is.
The regression analysis module performs comprehensive analysis according to the scanning uploading fluctuation coefficient, the vibration updating period floating coefficient and the alarm response evaluation coefficient, establishes a management model, calculates the confidence deviation index of the intelligent alarm evaluation system of the transformer substation monitoring system, and calculates the confidence deviation index as followsIn which, in the process,Scanning and uploading the scaling factors of the fluctuation coefficient, the vibration update period floating coefficient and the alarm response evaluation coefficient, andAre all greater than 0;
The expression of the confidence deviation index shows that the scanning uploading fluctuation coefficient can sense the frequency distribution range of the transformer insulation oil pressure monitoring, the vibration updating period floating coefficient evaluates the vibration period deviation degree of the power equipment, the alarm response evaluation coefficient comprehensively considers the inspection accuracy of the alarm system, wherein the F value directly represents the accuracy and recall rate of alarm prediction, and the operation stability and instantaneity of the intelligent alarm evaluation system of the transformer substation monitoring system can be effectively judged through the comprehensive evaluation of the scanning uploading fluctuation coefficient, the vibration updating period floating coefficient and the alarm response evaluation coefficient, the system operation failure is avoided, and the workload of staff is lightened;
the threshold value comparison module compares the calculated confidence deviation index of the intelligent alarm evaluation system of the transformer substation monitoring system with a preset confidence deviation index threshold value, if the calculated confidence deviation index is larger than or equal to the preset confidence deviation index, a sensitive signal is generated, and if the calculated confidence deviation index is smaller than the preset confidence deviation index, a steady-state signal is generated;
The early warning notification module performs processing strategy analysis according to the sensitive signals generated by the threshold comparison module, after receiving the sensitive signals generated by the threshold comparison module, the early warning notification module integrates and generates a data set according to a plurality of continuous confidence deviation index data of an evaluation system of intelligent warning of a transformer substation monitoring system within T time after the sensitive signals are generated, and the confidence deviation index in the data set is calibrated to be Rv, wherein v is the confidence deviation index number, namely Wherein x is a positive integer;
Calculating standard deviation of a plurality of confidence deviation indexes in a data set, calibrating the standard deviation of the confidence deviation indexes as So, comparing the standard deviation of the confidence deviation indexes with a preset standard deviation threshold Do of the confidence deviation indexes, and performing early warning processing according to comparison results, wherein the processing logic is as follows:
If So is greater than or equal to Do, marking an evaluation system for intelligent alarm of a substation monitoring system as a high risk level, prompting staff that the evaluation system for intelligent alarm of the substation monitoring system has an unreliable risk hidden danger, and detecting and maintaining are needed;
if So is smaller than Do, marking the evaluation system for intelligent alarm of the substation monitoring system as a low risk level, prompting staff that the evaluation system for intelligent alarm of the substation monitoring system has low risk hidden danger, and no detection and maintenance are needed.
According to the invention, through detecting the confidence deviation index of the intelligent alarm evaluation system of the transformer substation monitoring system, when the occurrence of abnormal data processing reliability is found, the subsequent operation state of the intelligent alarm evaluation system of the transformer substation monitoring system is comprehensively analyzed, the abnormal hidden danger is judged, and an early warning prompt is sent, so that a worker can be effectively assisted to acquire the potential hidden danger state, the potential hidden danger is checked and solved in advance, the operation effectiveness of the evaluation system is prevented from entering the invisible failure state, the workload of the worker is reduced, and the management efficiency is improved.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired or wireless means (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
It should be understood that, in various embodiments of the present application, the sequence numbers of the foregoing processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation process of the embodiments of the present application.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, reference may be made to the corresponding process in the foregoing method embodiment for the specific working process of the above-described system, which is not described herein again.
The functions, if implemented in the form of software functional units and sold or used as stand-alone goods, may be stored in a computer readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in the form of software goods stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (8)
1. The evaluation system of the intelligent alarm of the transformer substation monitoring system is characterized by comprising an element grabbing module, a regression analysis module, a threshold value comparison module and an early warning notification module;
the element grabbing module is used for collecting induction precision information and evaluation trust information of an evaluation system of intelligent alarm of the substation monitoring system and transmitting the induction precision information and the evaluation trust information to the regression analysis module;
The regression analysis module is used for comprehensively analyzing the induction precision information and the evaluation trust information, establishing an analysis model, and calculating the confidence deviation index of the evaluation system of the intelligent alarm of the substation monitoring system by using a logistic regression method;
the threshold value comparison module is used for comparing the calculated confidence deviation index with a preset confidence deviation index, and carrying out signal classification on the detection state reliability of the evaluation system of the intelligent alarm of the transformer substation monitoring system according to the comparison result;
The early warning notification module is used for carrying out early warning processing according to the signal type of the evaluation system of the intelligent warning of the transformer substation monitoring system.
2. The system for evaluating intelligent alarms of a substation monitoring system according to claim 1, wherein the sensing precision information comprises a scanning uploading fluctuation coefficient and a vibration updating period floating coefficient, and the evaluation trust information is an alarm response evaluation coefficient.
3. The system for evaluating intelligent alarms of a substation monitoring system according to claim 2, wherein the calculation method of the scanning uploading fluctuation coefficient is as follows:
S101, acquiring the scanning uploading frequency of the intelligent alarm of the substation monitoring system, wherein the scanning uploading frequency of the pressure sensor is operated by the intelligent alarm evaluation system of the substation monitoring system in the T time, calibrating the monitoring frequency of the scanning uploading frequency of the pressure sensor operated by the intelligent alarm evaluation system of the substation monitoring system in the T time as Tr, and r is the number of the scanning uploading frequency of the pressure sensor operated by the intelligent alarm evaluation system of the substation monitoring system in the T time, wherein the number of the scanning uploading frequency of the pressure sensor is calculated by the intelligent alarm evaluation system of the substation monitoring system in the T time, and Wherein e is a positive integer;
s102, acquiring a minimum scanning uploading frequency value of the intelligent alarm of the substation monitoring system, wherein the minimum scanning uploading frequency value of the pressure sensor is operated by the intelligent alarm evaluation system of the substation monitoring system in the T time, and calibrating the minimum scanning uploading frequency value of the pressure sensor by the intelligent alarm evaluation system of the substation monitoring system in the T time as La;
s103, the pair meets The method comprises the steps that scanning uploading frequency of a pressure sensor operated by an evaluation system of intelligent warning of a transformer substation monitoring system in T time is extracted and integrated into a low-frequency data set, the low-frequency data set is numbered to be Pl according to a time sequence of the scanning uploading frequency of the pressure sensor, which is acquired by the evaluation system of intelligent warning of the transformer substation monitoring system in T time, l is the data number, andWherein j is a positive integer;
S104, calculating the expression of the scanning uploading fluctuation coefficient as follows 。
4. The system for evaluating intelligent alarms of a substation monitoring system according to claim 2, characterized in that the method for calculating the floating coefficient of the vibration update period is as follows:
S201, acquiring a reasonable error range of a vibration monitoring period of an evaluation system of the intelligent alarm of the transformer substation monitoring system, and calibrating the reasonable error range of the vibration monitoring period of the evaluation system of the intelligent alarm of the transformer substation monitoring system to be Vi1-Vi2;
s202, acquiring a vibration monitoring period of an evaluation system of intelligent alarm of a substation monitoring system, and calibrating data of the vibration monitoring period of the evaluation system of intelligent alarm of the substation monitoring system as Vb;
S203, integrating a plurality of vibration monitoring period data of the transformer substation monitoring system intelligent alarm evaluation system in the T time into a data set, and marking the serial numbers of the vibration monitoring water level data with b, namely Wherein g is a positive integer;
s204, calculating the standard deviation of the vibration monitoring period data set, and then obtaining the standard deviation In which, in the process,For the average value of the vibration monitoring period data set, the calculation expression is；
S205, calculating the expression of the vibration update period floating coefficient as。
5. The system for evaluating intelligent alarms of a substation monitoring system according to claim 2, wherein the calculation method of the alarm response evaluation coefficient is as follows:
s301, setting a preset reference value for a comprehensive evaluation index of alarm accuracy of an evaluation system of intelligent alarm of a transformer substation monitoring system in T time, and calibrating the preset reference value of the comprehensive evaluation index to be Bu, wherein Bu is larger than 1;
the preset reference value of the comprehensive evaluation index ranges from 0 to 1, and indexes of the matching accuracy P and the recall R can be comprehensively considered;
S302, acquiring comprehensive evaluation indexes of the intelligent alarm evaluation system of the substation monitoring system in different time periods within the T time, calibrating the comprehensive evaluation indexes to be Ax, wherein x represents the number of the comprehensive evaluation indexes of the intelligent alarm evaluation system of the substation monitoring system of the game background user in different time periods within the T time, and P is a positive integer;
The expression of the comprehensive evaluation index calculation is that In the formula, P represents the matching accuracy, the judging accuracy refers to the proportion of the abnormal state in the evaluation system of the intelligent alarm of the substation monitoring system, which is judged to be in the abnormal state, and the calculating method comprises the following steps: matching accuracy = number of abnormal states correctly matched/number of all abnormal states determined, R represents recall, which refers to the ratio between the number of abnormal states correctly matched by the evaluation system of the intelligent alarm of the substation monitoring system and the number of all actual abnormal states, and the calculation method is as follows: recall = number of abnormal states correctly matched/number of all actual abnormal states;
the number of the abnormal states is the number of the abnormal states which are judged by the intelligent alarms of the substation monitoring system in a certain time range, wherein the real abnormal states and the misjudged normal states are included, the detection states are generally classified and marked by the intelligent alarms of the substation monitoring system, or the abnormal judgment conditions of transactions are recorded in a log, and the abnormal judgment conditions can be obtained by counting the number of the abnormal states marked by the intelligent alarms of the substation monitoring system;
The number of all actual abnormal states refers to the number of all abnormal states existing under the actual condition, and the actual abnormal states are possibly caused by detection and judgment errors, so that an evaluation system of intelligent alarm of a transformer substation monitoring system needs to interact with a power terminal server or a database to acquire the number of the actual abnormal states;
s303, calculating an expression of an alarm response evaluation coefficient as follows 。
6. The system for evaluating intelligent alarms of a substation monitoring system according to claim 2, wherein the method for calculating the confidence deviation index of the system for evaluating intelligent alarms of a substation monitoring system is as follows:
The regression analysis module performs comprehensive analysis according to the scanning uploading fluctuation coefficient, the vibration updating period floating coefficient and the alarm response evaluation coefficient, establishes a management model, calculates the confidence deviation index of the intelligent alarm evaluation system of the transformer substation monitoring system, and calculates the confidence deviation index as follows In which, in the process,Scanning and uploading the scaling factors of the fluctuation coefficient, the vibration update period floating coefficient and the alarm response evaluation coefficient, andAre all greater than 0.
7. The system for evaluating intelligent alarms of a substation monitoring system according to claim 6, wherein the logic for classifying signals for the reliability of the detection status of the system for evaluating intelligent alarms of a substation monitoring system is:
Comparing the calculated confidence deviation index of the intelligent alarm evaluation system of the transformer substation monitoring system with a preset confidence deviation index threshold, generating a sensitive signal if the calculated confidence deviation index is greater than or equal to the preset confidence deviation index, and generating a steady-state signal if the calculated confidence deviation index is less than the preset confidence deviation index.
8. The intelligent alarm evaluation system for a substation monitoring system according to claim 7, wherein the logic for performing the early warning processing on the intelligent alarm evaluation system for the substation monitoring system is:
The early warning notification module performs processing strategy analysis according to the sensitive signals generated by the threshold comparison module, after receiving the sensitive signals generated by the threshold comparison module, the early warning notification module integrates and generates a data set according to a plurality of continuous confidence deviation index data of an evaluation system of intelligent warning of a transformer substation monitoring system within T time after the sensitive signals are generated, and the confidence deviation index in the data set is calibrated to be Rv, wherein v is the confidence deviation index number, namely Wherein x is a positive integer;
Calculating standard deviation of a plurality of confidence deviation indexes in a data set, calibrating the standard deviation of the confidence deviation indexes as So, comparing the standard deviation of the confidence deviation indexes with a preset standard deviation threshold Do of the confidence deviation indexes, and performing early warning processing according to comparison results, wherein the processing logic is as follows:
If So is greater than or equal to Do, marking an evaluation system for intelligent alarm of a substation monitoring system as a high risk level, prompting staff that the evaluation system for intelligent alarm of the substation monitoring system has an unreliable risk hidden danger, and detecting and maintaining are needed;
if So is smaller than Do, marking the evaluation system for intelligent alarm of the substation monitoring system as a low risk level, prompting staff that the evaluation system for intelligent alarm of the substation monitoring system has low risk hidden danger, and no detection and maintenance are needed.
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