CN107437113B - Distribution main equipment live-line detection criterion knowledge base system and implementation method thereof - Google Patents
Distribution main equipment live-line detection criterion knowledge base system and implementation method thereof Download PDFInfo
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Abstract
The invention provides a method for realizing a power distribution main equipment live detection criterion knowledge base system, which comprises the following steps: (1) acquiring data to be judged by using charged detection equipment; (2) preprocessing the data to be judged; (3) judging the data to be judged by applying a judging method to obtain a judging result; (4) matching the judgment result with a judgment rule; (5) and updating the expert knowledge base according to the updating rule. The expert knowledge base system integrates the functions of electrified detection fault information characteristic classification, fault information normalization processing, fault information characteristic indexing and inquiring, fault type judging and identifying, fault statistics, cyclic ratio analysis and the like of the power distribution main equipment, and improves the electrified detection accuracy and efficiency of the power distribution main equipment.
Description
Technical Field
The invention relates to a detection criterion knowledge base system and an implementation method thereof, in particular to a distribution main equipment live-line detection criterion knowledge base system and an implementation method thereof.
Background
Distribution equipment is of great importance in urban power grids, and the availability rate of the distribution equipment directly influences the reliability of power supply. Statistics shows that most of power failure accidents in the power system are caused by power distribution equipment faults, so that the equipment availability can be remarkably improved by effectively detecting and judging the power distribution equipment faults. The traditional power distribution equipment fault detection adopts periodic preventive tests, has the defects of high proportion of total power failure time occupied by the power failure tests, low fault detection accuracy, overlong maintenance interval time and the like, and can fundamentally solve the defects of the traditional detection method due to the occurrence of the electrified detection technology of the power distribution equipment.
At present, the method for detecting the electrification of the power distribution equipment mainly comprises an infrared temperature measurement method, a TEV and ultrasonic partial discharge test method, a high-frequency partial discharge test method and the like. However, the distribution equipment has various types and complex structures, is limited to the fault characteristic differences of different electrical elements and the transmission characteristic differences caused by different equipment structures, and has no technical means which can be widely applied to the live detection of the distribution equipment, and needs to jointly apply various testing tools and data analysis methods to carry out fault judgment. However, the data to be processed in the live detection is complex in source, large in information amount and various in types, and not only is the workload huge due to the fact that the data is simply judged by manpower, but also misjudgment and missed judgment can be caused due to the limitation of the technical experience of operation and maintenance detection personnel, and the live detection efficiency and accuracy are affected.
Along with the continuous expansion of the scale of the power distribution network and the continuous improvement of the power supply reliability requirements of power customers, the requirements of operation and maintenance teams in the power distribution network base level on the electrified detection work such as infrared temperature measurement, ultrasonic partial discharge detection, transient ground voltage partial discharge detection and the like are increasingly urgent. However, at present, no electrified detection auxiliary judgment and analysis tool which is not limited by the technical experience of operation and maintenance detection personnel and has high identification accuracy and can comprehensively apply various electrified detection data to judge and identify the faults of the distribution equipment exists, so that the wide application of the electrified detection technology of the distribution equipment is influenced, and the popularization and application of the electrified detection work are influenced.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a power distribution main equipment live detection criterion knowledge base system and an implementation method thereof.
In order to achieve the purpose of the invention, the invention adopts the following technical scheme:
a method for realizing a power distribution main equipment live detection criterion knowledge base system comprises the following steps:
(1) acquiring data to be judged by using charged detection equipment;
(2) preprocessing the data to be judged;
(3) judging the data to be judged by applying a judging method to obtain a judging result;
(4) matching the judgment result with a judgment rule;
(5) and updating the expert knowledge base according to the updating rule.
Preferably, in the step (1), the data to be determined includes the model, the manufacturer, and the operating life of the device to be detected, and the detection data.
Preferably, in the step (2), the data obtained by the live detection includes amplitude data and spectrum data, the amplitude data needs to be corrected before the fault determination, and the spectrum data needs to keep consistent with a statistical method.
Preferably, in the step (3), the determination method includes a threshold method, a trend method, a comparison determination method and a spectrum fingerprint method; the threshold method is used for obtaining a judgment conclusion according to the comparison analysis result of the detection data and the set limit value; the trend method is that the change rate and the change trend of the fault characteristic quantity are analyzed according to the detection data of the same equipment at different time, and the actual state of the equipment is judged; the comparison and judgment method is characterized in that longitudinal and transverse comparison is carried out according to test data of the same equipment at different times or the same equipment, and the change trend and the actual state of the fault characteristics are judged, wherein the former is called longitudinal comparison and judgment, and the latter is called transverse comparison and judgment; the atlas fingerprint method is characterized in that an atlas fingerprint library is established according to the defect types of equipment, different types of defects are stored in corresponding atlas fingerprint sub-libraries to serve as judgment references, atlas data and atlases in the atlas fingerprint library are compared one by one, and the atlas fingerprint sub-library with the maximum correlation degree serves as a judgment result.
Preferably, the threshold method is applied to amplitude class data, and the spectrum fingerprint method is applied to spectrum class data; the trend method and the comparison judgment method are used as qualitative auxiliary analysis methods.
Preferably, in the step (4), for the amplitude class data, the rule is determined to be a threshold interval of different fault states, and the matching is successful within the threshold interval; and for the atlas data, the judgment rule is the similarity between the atlas and the sample atlas in different fault states, and the matching is successful if the atlas with the maximum correlation degree with the atlas data is found in the atlas fingerprint database.
Preferably, in the step (5), the updating rule includes:
for the judgment of the atlas fingerprint method, the updating of the expert knowledge base and the confirmation of the judgment result are carried out synchronously;
for the judgment of the threshold value method, when the confirmation times of the judgment results of the single-type detection data are more than or equal to 100 times, updating the judgment rules of the expert knowledge base based on the updating basis; the updating basis is as follows: if the accuracy of the judgment result is greater than or equal to 95%, keeping the original set threshold unchanged; and if the accuracy of the judgment result is less than 95%, increasing or reducing the original set threshold.
Preferably, a power distribution main equipment live detection criterion knowledge base system includes: the system comprises an information input module, an expert knowledge base module, a comprehensive evaluation module, a statistical analysis module, a comprehensive query module and a system management module;
the system comprises an information input module, a detection device information input module, a detection material input module and a display module, wherein the information input module is used for receiving charged detection data, the information input module comprises the detection information input module and the detection material input module, the detection information input module is used for detecting the input of basic information, detection device information and detection instrument information, and the detection material input module is used for inputting charged detection data materials and displaying the charged detection data materials in a list form;
the expert knowledge base module comprises an expert knowledge base management module and an expert knowledge base, the expert knowledge base management module configures, changes and maintains the expert knowledge base based on equipment types, fault types, detection methods and fault characteristics, and the expert knowledge base is used for storing equipment information, fault type information, detection method information, fault characteristic information and corresponding maintenance suggestions;
the comprehensive evaluation module comprises a fault identification and analysis module and a judgment module, wherein the fault identification and analysis module is used for referring to the overhaul record or the defect record in the expert knowledge base aiming at the electrified detection data material, calling a fault identification and analysis algorithm and judging and analyzing the current fault state of the equipment to be tested; the judging module is used for providing a fault judging result and a judging process information query function;
the statistical analysis module is used for carrying out comparison and ring ratio analysis on the live detection records of the same equipment and the similar equipment, providing failure month frequency statistics and annual trend analysis, and transmitting analysis information to the comprehensive query module;
the comprehensive query module provides functions of detecting standards, detecting basic information, detecting materials, detecting equipment defects and inquiring overhaul records;
the system management module provides user group maintenance, user maintenance, log management, module function maintenance, data backup and recovery functions.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides an expert knowledge base system for electrified detection criteria of power distribution main equipment, which integrates the functions of electrified detection fault information characteristic classification, fault information normalization processing, fault information characteristic indexing and inquiring, fault type judgment and identification, fault statistics, cyclic ratio analysis and the like of the power distribution main equipment into a whole, has the advantages of high response speed, convenient management and maintenance, abundant data samples, good compatibility, strong practicability and expansibility, and obviously improves the accuracy and efficiency of electrified detection of the power distribution main equipment.
Drawings
FIG. 1 is a relational diagram of an expert knowledge base system for power distribution main equipment live detection criteria provided by the invention,
FIG. 2 is a block diagram of an expert knowledge base system for power distribution main equipment live-line detection criteria provided by the present invention,
fig. 3 is a flowchart of an implementation method of the expert knowledge base system for power distribution main equipment live detection criteria provided by the invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
As shown in fig. 1, the power distribution main equipment live-line detection criterion expert knowledge base system provided by the invention comprises an information input module, an expert knowledge base module, a comprehensive evaluation module, a statistical analysis module, a comprehensive query module and a system management module.
As shown in fig. 2, the information entry module is a structural diagram of the expert knowledge base system provided by the present invention. The system comprises a detection information input module and a detection material input module.
The detection information input module comprises functions of detecting basic information input, detecting equipment information input and detecting instrument information input. The detection basic information comprises detection personnel, the number of the detection personnel, the department to which the detection personnel belongs, detection position information (detail addresses of provinces, cities, districts and streets, GPRS longitude and latitude) and detection environment information (time, weather, temperature, humidity and wind speed); the detection equipment information comprises equipment name, equipment model, equipment nameplate information and equipment image; the detection instrument information respectively aims at different detection instrument types and comprises detection range, precision, working temperature, working humidity and matched accessory information.
The detection material recording module has a charged detection data material (data, waveform and map) recording function and can display recorded detection material information in a list form. The detection material information is different according to different types of detection instruments.
The expert knowledge base module comprises an expert knowledge base management module and an expert knowledge base, the expert knowledge base management module configures, changes and maintains the expert knowledge base based on the equipment type, the fault type, the detection method and the fault characteristics, and the expert knowledge base is used for storing equipment information, fault type information, detection method information, fault characteristic information and corresponding maintenance suggestions;
the device type module provides a device type list, can inquire the detailed information of all devices under the type according to the device type, and can perform adding, modifying and deleting operations on the device information.
The fault type module provides a device type list, can inquire the detailed information of all fault types under the type according to the device type, and can perform addition, modification and deletion operations on the fault type information.
The detection method module provides maintenance function of each fault type detection method, selects a certain fault type to inquire all detection method information of the fault type, and the administrator can add, modify and delete the detection method.
The fault characteristic module provides fault characteristic information of each fault type and a maintenance function of a corresponding maintenance suggestion, and an administrator can perform adding, modifying and deleting operations of the fault characteristic information and the corresponding maintenance suggestion.
And a comprehensive evaluation module. The system comprises a fault identification and analysis module and a judgment result module.
And the fault identification and analysis module refers to the overhaul record or the defect record aiming at the live detection actual measurement material, calls a fault identification and analysis algorithm, judges and analyzes the current fault state of the equipment to be detected, and provides a judgment result and a maintenance suggestion.
And the judgment result module provides a fault judgment result and a judgment process information query function.
And the statistical analysis module is used for comparing and analyzing the live detection records (faults in the same period and the same type) of the same equipment and the similar equipment, providing fault month number statistics and annual trend analysis and providing fault judgment detailed information inquiry and checking functions.
And the comprehensive query module provides functions of detecting standard, detecting basic information, detecting material, detecting equipment defects and inquiring overhaul records.
The standard query module provides query and viewing functions of standards, specifications or guidelines related to the live detection technology.
The detection basic information query module can query and check historical detection data according to the equipment type, the detection instrument, the detection time and the information of detection personnel. Meanwhile, the administrator can identify and analyze the fault based on the basic detection information and select whether to store the detection record into the expert knowledge base.
The detection material inquiry module provides a detection material list information inquiry function.
And the equipment defect and maintenance record query module provides a function of querying historical data of the detected basic information.
And the system management module provides user group maintenance, user maintenance, log management, module function maintenance and data backup and recovery functions.
As shown in fig. 3, a method for implementing an expert knowledge base system for power distribution main equipment live-line detection criteria includes the following specific steps:
step 1, acquiring data to be judged by using electrified detection equipment;
and the electrified detection data is acquired by electrified detection equipment such as infrared temperature measurement, ultrasonic waves, TEV, high frequency and the like. The data to be judged comprises basic information such as equipment model, manufacturer, operation year and the like and corrected detection data.
Step 2, preprocessing the data to be judged;
before fault judgment, amplitude data needs to be corrected, and atlas data needs to keep consistent statistical methods.
Step 3, judging the data to be judged by applying a judging method to obtain a judging result;
and matching the detection data with the judgment rule by using the sample information of the knowledge base according to the electrified detection data currently received by the knowledge base system and applying a fault judgment method, and obtaining a conclusion after the matching is successful.
The failure determination method comprises the following steps: including threshold methods, trend methods, comparison and judgment methods and spectrum fingerprint methods.
The threshold value method is suitable for amplitude class data, and the spectrum fingerprint method is suitable for spectrum class data; a trend method and a comparison judgment method are used as qualitative auxiliary analysis methods.
The threshold method is to give a decision based on the comparison analysis result (approaching or exceeding) of the detected data and the set limit value.
The threshold method is generally used to determine whether a device is faulty or not, and also to determine the severity of the fault, the type of the fault, and the cause of the fault.
The trend method is to analyze the change rate and the change trend of the fault characteristic quantity according to the detection data of the same equipment at different times and judge the actual state of the equipment.
The comparison and judgment method is to compare longitudinally and transversely according to different times of the same equipment or test data of the same equipment, and judge the change trend and the actual state of the fault characteristics of the equipment. The former is called longitudinal contrast determination, and the latter is called lateral contrast determination.
The atlas fingerprint method is to establish atlas fingerprint library based on the equipment defect type and to store different kinds of defect in corresponding atlas fingerprint sub-library as judgment reference. And comparing the to-be-determined atlas with the atlases in the atlas fingerprint library one by one, and taking the atlas fingerprint sub-library with the maximum correlation as a determination result.
Step 4, matching the judgment result with a judgment rule;
and (3) judging rules: for amplitude class data, threshold intervals of different fault states are defined; and for the atlas data, the similarity with the atlas of different fault states is shown.
And 5, updating the expert knowledge base according to the updating rule.
And confirming whether the fault type is consistent with the judgment result of the expert knowledge base or not by the operation and maintenance personnel on the equipment operation site according to the fault judgment result.
And inputting the determined judgment data and judgment results into the expert knowledge base as effective samples and updating the expert knowledge base.
If the judgment result is not correct, the judgment data and the judgment result are stored in a database to be confirmed for waiting, and after the confirmation is finished, the judgment data and the judgment result are input into an expert knowledge base for updating.
For the judgment performed by using the atlas fingerprint method, the updating of the expert knowledge base and the confirmation of the judgment result are performed synchronously without manual intervention.
For the judgment using the threshold method, when the number of times of confirmation of the judgment result of the single-type detection data is equal to or more than 100 times, the judgment rule of the expert knowledge base can be updated.
Updating the basis: if the accuracy of the judgment result is more than or equal to 95%, keeping the original set threshold unchanged; and if the accuracy of the judgment result is less than 95%, increasing or reducing the original set threshold.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (4)
1. A method for realizing a power distribution main equipment live detection criterion knowledge base system is characterized by comprising the following steps:
(1) acquiring data to be judged by using charged detection equipment;
(2) preprocessing the data to be judged;
(3) judging the data to be judged by applying a judging method to obtain a judging result;
(4) matching the judgment result with a judgment rule;
(5) updating the expert knowledge base according to the updating rule;
in the step (3), the judging method comprises a threshold value method, a trend method, a comparison judging method and a spectrum fingerprint method; the threshold method is used for obtaining a judgment conclusion according to the comparison analysis result of the detection data and the set limit value; the trend method is that the change rate and the change trend of the fault characteristic quantity are analyzed according to the detection data of the same equipment at different time, and the actual state of the equipment is judged; the comparison and judgment method is characterized in that longitudinal and transverse comparison is carried out according to test data of the same equipment at different times or the same equipment, and the change trend and the actual state of the fault characteristics are judged, wherein the former is called longitudinal comparison and judgment, and the latter is called transverse comparison and judgment; the atlas fingerprint method is characterized in that an atlas fingerprint library is established according to the defect types of equipment, different types of defects are stored in corresponding atlas fingerprint sub-libraries to be used as judgment references, atlas data and atlases in the atlas fingerprint library are compared one by one, and the atlas fingerprint sub-library with the maximum correlation degree is used as a judgment result;
the threshold value method is suitable for amplitude class data, and the spectrum fingerprint method is suitable for spectrum class data; the trend method and the comparison judgment method are used as qualitative auxiliary analysis methods;
in the step (4), for the amplitude data, the rule is judged to be a threshold interval of different fault states, and the matching is successful in the threshold interval; for the atlas data, the judgment rule is the similarity between the atlas and the sample atlas in different fault states, and if the atlas with the maximum correlation degree with the atlas data is found in the atlas fingerprint database, the matching is successful;
in the step (5), the updating rule includes:
for the judgment of the atlas fingerprint method, the updating of the expert knowledge base and the confirmation of the judgment result are carried out synchronously;
for the judgment of the threshold value method, when the confirmation times of the judgment results of the single-type detection data are more than or equal to 100 times, updating the judgment rules of the expert knowledge base based on the updating basis; the updating basis is as follows: if the accuracy of the judgment result is greater than or equal to 95%, keeping the original set threshold unchanged; and if the accuracy of the judgment result is less than 95%, increasing or reducing the original set threshold.
2. The method according to claim 1, wherein in the step (1), the data to be determined includes basic information of the model, the manufacturer and the operating life of the device to be tested, and the test data.
3. The method according to claim 2, wherein in the step (2), the data obtained by the live detection comprises amplitude class data and pattern class data, the amplitude class data needs to be corrected before the fault determination, and the pattern class data needs to be kept consistent with a statistical method.
4. A power distribution main equipment live detection criterion knowledge base system for implementing the method of claim 1, the system comprising: the system comprises an information input module, an expert knowledge base module, a comprehensive evaluation module, a statistical analysis module, a comprehensive query module and a system management module;
the system comprises an information input module, a detection device information input module, a detection material input module and a display module, wherein the information input module is used for receiving charged detection data, the information input module comprises the detection information input module and the detection material input module, the detection information input module is used for detecting the input of basic information, detection device information and detection instrument information, and the detection material input module is used for inputting charged detection data materials and displaying the charged detection data materials in a list form;
the expert knowledge base module comprises an expert knowledge base management module and an expert knowledge base, the expert knowledge base management module configures, changes and maintains the expert knowledge base based on equipment types, fault types, detection methods and fault characteristics, and the expert knowledge base is used for storing equipment information, fault type information, detection method information, fault characteristic information and corresponding maintenance suggestions;
the comprehensive evaluation module comprises a fault identification and analysis module and a judgment module, wherein the fault identification and analysis module is used for referring to the overhaul record or the defect record in the expert knowledge base aiming at the electrified detection data material, calling a fault identification and analysis algorithm and judging and analyzing the current fault state of the equipment to be tested; the judging module is used for providing a fault judging result and a judging process information query function;
the statistical analysis module is used for carrying out comparison and ring ratio analysis on the live detection records of the same equipment and the similar equipment, providing failure month frequency statistics and annual trend analysis, and transmitting analysis information to the comprehensive query module; the comprehensive query module provides functions of detecting standards, detecting basic information, detecting materials, detecting equipment defects and inquiring overhaul records;
the system management module provides user group maintenance, user maintenance, log management, module function maintenance, data backup and recovery functions.
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| CN112036704B (en) * | 2020-08-04 | 2023-11-28 | 南方电网调峰调频发电有限公司 | Power equipment fault management system |
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| CN113377794B (en) * | 2021-06-23 | 2023-04-18 | 云南电网有限责任公司电力科学研究院 | Database autonomous learning method and database applying same |
| CN113592367A (en) * | 2021-09-27 | 2021-11-02 | 广东电网有限责任公司 | Fault detection method and device based on multiple system data |
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