CN117607531A - Transformer substation direct current system fault investigation system and investigation method thereof - Google Patents
Transformer substation direct current system fault investigation system and investigation method thereof Download PDFInfo
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Abstract
The invention belongs to the technical field of fault investigation of transformer substations, and discloses a fault investigation system of a direct current system of a transformer substation. According to the invention, through realizing pre-interference processing in advance, fault problems are roughly handled, the probability and effect of fault investigation and repair are improved, and through an intelligent decision support module, an expert system and a rule base are introduced before complete result diagnosis is completed according to the state of a direct current system and the primary result of fault diagnosis, an intelligent decision-making fault maintenance method is adopted, a personalized maintenance scheme and a test scheme are generated according to specific conditions, and a detailed decision basis is provided, so that the decision making capability and the strain capability of a fault investigation system are improved, and the prediction capability and the decision making capability of the system for fault investigation and maintenance are greatly improved.
Description
Technical Field
The invention belongs to the technical field of fault investigation of transformer substations, and particularly relates to a fault investigation system and a fault investigation method for a direct current system of a transformer substation.
Background
The direct current system of the transformer substation is a very important part in the transformer substation and is generally used for providing reliable direct current power supply for various devices in the transformer substation, such as relay protection equipment, control equipment, communication equipment and the like, is particularly important for troubleshooting the direct current system of the transformer substation, and is convenient for timely maintenance so as to restore normal operation.
In the prior art, in the fault investigation system of the transformer substation direct current system, data collection is usually incomplete, equipment monitoring coverage in the corresponding direct current system is limited, the traditional fault investigation system can only acquire limited data and cannot comprehensively know the state and parameters of each equipment, the traditional fault investigation method is usually only stopped at the location of a fault point, deep analysis on fault reasons is lacking, in the fault investigation process of different faults, database comparison of faults of each direct current system is insufficient, different fault conditions of equipment in different direct current systems are treated, accurate and effective matching is difficult to achieve, the location and evaluation effects of actual fault problems are poor, and the comprehensive investigation and determination and fault elimination effects are poor in the fault investigation of the transformer substation direct current system.
Disclosure of Invention
The invention aims to provide a fault checking system and a fault checking method for a direct current system of a transformer substation, which are used for solving the problems in the background technology.
In order to achieve the above object, the present invention provides the following technical solutions: the system comprises a data acquisition module, a data processing and analyzing module, a fault diagnosis module, a predictive maintenance module, an intelligent decision support module, a fault positioning auxiliary module and a maintenance and test module,
the data acquisition module comprises a sensor, a detection device and a detection object, wherein the data acquisition module acquires parameter data in a direct current system, the parameter data comprise voltage, current, temperature and grounding current, and the data are sent to the data processing module for processing and storage;
the data processing and analyzing module comprises a data storage device unit, a data processing algorithm unit and a database management system, and is used for receiving the data from the data acquisition module and processing, analyzing and storing the data;
the fault diagnosis module comprises a fault diagnosis algorithm, a fault condition, a topological structure and a connection relation unit, performs fault diagnosis and positioning according to the information provided by the data processing and analyzing module, and helps to determine the position and the reason of the fault by combining the topological structure of the direct current system with the connection relation of equipment;
the predictive maintenance module comprises a machine learning algorithm, a data mining unit and a preprocessing operation library, and utilizes the machine learning and data mining technology to predict and evaluate the equipment state of the direct current system by combining the historical data and the real-time data of the data acquisition module and the result data of the fault diagnosis module so as to discover potential fault signs in advance;
the intelligent decision support module comprises an expert system and a decision tree algorithm unit, integrates the expert system and the decision tree algorithm, provides fault processing suggestions and schemes for operators according to real-time monitoring data of the data acquisition module and fault diagnosis results of the fault diagnosis module, and assists the operators in making decisions;
the fault positioning auxiliary module comprises real-time monitoring equipment and a remote assistance unit, wherein the real-time monitoring equipment comprises a thermal infrared imager and partial discharge detection equipment, and the remote assistance support unit comprises an AR technology and a VR technology.
Preferably, the detection object comprises rectifying equipment, a control protection system, a direct current circuit and a battery pack, the fault condition comprises rectifying equipment faults, direct current circuit faults, battery pack faults and control protection system faults, the rectifying equipment comprises a rectifying transformer and a rectifying module, the direct current circuit comprises a direct current bus, a direct current switch and an isolating switch, the control protection system comprises a control protection device and a communication device, and the battery pack comprises a storage battery, a battery cabinet, a fan, a radiator and a filter.
Preferably, the wireless sensor network protocol adopted by the data acquisition module is LoRaWAN, and the data acquisition module adopts wireless sensor nodes and a base station to transmit data to the system evaluation module.
Preferably, the data processing and analyzing module is an internal communication protocol, the internal communication protocol adopted by the data processing and analyzing module is an internal bus protocol I2C, and the data processing and analyzing module adopts an ethernet to transmit data to the fault identifying and positioning module.
Preferably, the fault diagnosis module comprises fault identification and fault positioning, wherein an internal bus protocol Modbus is connected between the fault identification and the fault positioning, and Ethernet data transmission is arranged between the fault diagnosis module and the maintenance and test module.
Preferably, the test contents of the maintenance and test module comprise fault discharge result determination, post-maintenance performance test and post-maintenance safety test.
A method for checking a fault checking system of a direct current system of a transformer substation comprises the following checking steps:
step one, data collection: collecting alarm information, equipment operation state and data information corresponding to the electrical parameters;
second step, preliminary analysis: performing preliminary analysis on the collected data to determine the possible range of occurrence of the problem;
third step, predictive maintenance: intercepting preliminary analysis data, calling a preprocessing operation library in a predictive maintenance module, and under the comparison of initial data, calling the closest preprocessing scheme from the preprocessing operation library to conduct predictive fault detection;
fourth, detailed investigation: obtaining a result of the preliminary analysis, performing on-site checking of equipment, analysis of equipment performance parameters and historical maintenance records, and further determining a fault point;
fifth step, fault location: the control and the investigation of the sections, the subsection positions and the subsection components are carried out through the inspection equipment and the inspection system, and finally the fault point is determined;
sixth, intelligent decision: intercepting detailed investigation data and fault positioning data, running a decision tree algorithm unit, automatically starting an expert system, and performing intelligent fault decision processing;
seventh, fault treatment: specific treatment schemes are formulated in detail according to fault conditions, wherein the specific treatment schemes comprise equipment replacement, parameter adjustment and equipment repair;
eighth step, verifying and retesting: after the treatment, the treatment scheme is verified, the running condition of the equipment is tested again, and the equipment is checked to be completely recovered to be normal.
The beneficial effects of the invention are as follows:
according to the invention, through a newly added predictive maintenance module and intelligent decision support module, based on historical data and a model established by a machine learning algorithm, possible faults of a direct current system can be predicted, maintenance is performed in advance, downtime and loss caused by the faults are avoided, under the condition of intercepting initial data, based on regression analysis and time sequence analysis, early pre-interference treatment is realized in the early stage of complete fault detection, fault detection and repair probability and effect are improved, and through the intelligent decision support module, according to the state of the direct current system and the initial result of fault diagnosis, an expert system and a rule base are introduced, an intelligent decision fault maintenance method is used for generating an individualized maintenance scheme and a test scheme according to specific conditions, and a detailed decision basis is provided, so that the decision capability and the strain capability of the fault detection system are improved, and the prediction capability and the decision capability of the fault detection and maintenance of the system are greatly improved.
Drawings
FIG. 1 is a block diagram of a system according to the present invention;
fig. 2 is a schematic diagram of the content of the acquisition object 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.
As shown in fig. 1 to 2, the embodiment of the invention provides a fault checking system and a checking method thereof for a direct current system of a transformer substation, wherein the system comprises a data acquisition module, a data processing and analyzing module, a fault diagnosis module, a predictive maintenance module, an intelligent decision support module, a fault positioning auxiliary module and a maintenance and test module,
the data acquisition module comprises a sensor, a detection device and a detection object, wherein the data acquisition module acquires parameter data in a direct current system, the parameter data comprise voltage, current, temperature and grounding current, and the data are sent to the data processing module for processing and storage;
the data processing and analyzing module comprises a data storage device unit, a data processing algorithm unit and a database management system, and is used for receiving the data from the data acquisition module and processing, analyzing and storing the data;
the fault diagnosis module comprises a fault diagnosis algorithm, a fault condition, a topological structure and a connection relation unit, performs fault diagnosis and positioning according to the information provided by the data processing and analyzing module, and helps to determine the position and the reason of the fault by combining the topological structure of the direct current system with the connection relation of equipment;
the predictive maintenance module comprises a machine learning algorithm, a data mining unit and a preprocessing operation library, and utilizes the machine learning and data mining technology to predict and evaluate the equipment state of the direct current system by combining the historical data and the real-time data of the data acquisition module and the result data of the fault diagnosis module so as to discover potential fault signs in advance;
the intelligent decision support module comprises an expert system and a decision tree algorithm unit, integrates the expert system and the decision tree algorithm, provides fault processing suggestions and schemes for operators according to real-time monitoring data of the data acquisition module and fault diagnosis results of the fault diagnosis module, and assists the operators in making decisions;
the fault positioning auxiliary module comprises real-time monitoring equipment and a remote assistance unit, wherein the real-time monitoring equipment comprises a thermal infrared imager and partial discharge detection equipment, and the remote assistance support unit comprises an AR technology and a VR technology.
In the use process, the sensor is used for collecting various parameter data of the direct current system in real time, such as voltage, current, temperature and the like, and the sensor can be a current sensor, a voltage sensor and a temperature sensor; the monitoring device is used for monitoring the state and the operation condition of the direct current system, such as a grounding current monitoring device, a battery state monitoring device and the like, and can be connected to the data processing module through a network.
The data acquisition module is responsible for monitoring and collecting operation data of the system, such as voltage, current, equipment state and the like in real time, collecting the data in an automatic mode, preprocessing the data, and removing invalid or erroneous data.
In the data processing and analyzing module, the data storage device is used for storing collected data, and can be a hard disk, a flash memory or cloud storage; the data processing algorithm is used for processing and analyzing the acquired data and can comprise algorithms such as filtering, fourier transformation, statistical analysis and the like; the database management system is used for managing and organizing stored data and providing inquiry and retrieval functions for historical data.
In the fault diagnosis module, a fault diagnosis algorithm diagnoses and positions faults through a series of fault diagnosis algorithms and rules based on data provided by the data processing and analysis module, wherein the algorithms can be expert systems based on rules or models based on machine learning; the fault diagnosis module needs to know the topological structure of the direct current system and the connection relation between the devices so as to assist in determining the position and possible reasons of the fault.
In the predictive maintenance module, a machine learning algorithm is used for predicting and evaluating by establishing a model and training and utilizing historical data and real-time data, and common algorithms comprise regression analysis, time sequence analysis, neural network and the like; data mining techniques are used to discover implicit patterns and rules from large amounts of data, helping to predict potential signs of failure.
In the intelligent decision support module, an expert system provides fault processing suggestions and schemes for operators according to real-time monitoring data and fault diagnosis results based on expert knowledge and a rule base; the decision tree algorithm models and optimizes the fault processing process by utilizing a decision tree model so as to assist operators to make decisions.
In the fault positioning auxiliary module, a real-time monitoring device, a thermal infrared imager, a partial discharge detection device and the like are used for helping operators to confirm fault points in the field, and the visual angle of a remote expert is shared with the field operators through an AR or VR technology, so that real-time communication and guidance are realized.
After the cause of the fault is determined, the maintenance and test module guides the repair work, and tests the system after the repair is completed, so as to verify the success of the repair.
The detection object comprises rectifying equipment, a control protection system, a direct current circuit and a battery pack, the fault condition comprises rectifying equipment faults, direct current circuit faults, battery pack faults and control protection system faults, the rectifying equipment comprises a rectifying transformer and a rectifying module, the direct current circuit comprises a direct current bus, a direct current switch and an isolating switch, the control protection system comprises a control protection device and communication equipment, and the battery pack comprises a storage battery, a battery cabinet, a fan, a radiator and a filter.
In the use process, checking parameters such as the state, temperature, input and output voltage, current and the like of the equipment, and the connection and grounding conditions of the equipment when the rectifying equipment is checked; checking the connection state, the line resistance and the insulation condition of the line when checking the straight line, and judging whether the problems of poor contact, open circuit and the like exist; checking the state and parameter setting of the protection device when checking the control protection system, and checking whether the connection state and signal transmission of the communication equipment are normal; and checking the voltage, capacity and internal resistance of the battery pack when checking the battery pack, and connecting states and charge and discharge control systems among the batteries.
The wireless sensor network protocol adopted by the data acquisition module is LoRaWAN, the data acquisition module adopts wireless sensor nodes and base stations to transmit data to the system evaluation module, the data processing and analysis module adopts an internal communication protocol, the internal communication protocol adopted by the data processing and analysis module is an internal bus protocol I2C, and the data processing and analysis module adopts Ethernet to transmit data to the fault recognition and positioning module.
In the use process, the data processing and analyzing module evaluates the collected data according to preset operation requirements and algorithms, and transmits the evaluation result to other modules, the data processing unit and the other modules are connected by using an internal bus protocol I2C so as to realize rapid internal data transmission, and the other modules are connected by using an Ethernet protocol through corresponding interfaces so as to realize external data transmission.
The fault diagnosis module comprises fault identification and fault positioning, wherein an internal bus protocol Modbus is connected between the fault identification and the fault positioning, ethernet data transmission is arranged between the fault diagnosis module and the maintenance and test module, and the test content of the maintenance and test module comprises fault discharge result determination, performance test after maintenance and safety test after maintenance.
A method for checking a fault checking system of a direct current system of a transformer substation comprises the following checking steps:
the first step: and (3) data collection: collecting alarm information, equipment operation state and data information corresponding to the electrical parameters;
the system operation condition is monitored in real time, fault alarm information is timely obtained, reliability and accuracy of data acquisition equipment are guaranteed during data collection, influences of data errors on fault investigation results are avoided, reasonable frequency and range of data acquisition are guaranteed, key equipment and electrical parameters are covered, safety and reliability of data transmission are guaranteed, and a data transmission process is protected by adopting an encryption and verification mechanism.
And a second step of: preliminary analysis: performing preliminary analysis on the collected data to determine the possible range of occurrence of the problem;
the method has the advantages that the fault type and possible reasons are rapidly judged, directions are provided for follow-up detailed investigation, reasonable analysis models and algorithms are established, data can be rapidly and accurately analyzed and processed, and effective data mining and fault pattern recognition are performed by combining historical data and experience knowledge.
Third step, predictive maintenance: intercepting preliminary analysis data, calling a preprocessing operation library in a predictive maintenance module, and under the comparison of initial data, calling the closest preprocessing scheme from the preprocessing operation library to conduct predictive fault detection;
fourth step: detailed investigation: according to the result of the preliminary analysis, performing on-site checking of the equipment, analysis of equipment performance parameters and historical maintenance records, and further determining fault points;
and carrying out detailed equipment inspection and test, including aspects of appearance, wiring, electrical parameters and the like, and knowing the running condition and maintenance condition of the equipment by combining the history record and maintenance log of the equipment.
Fifth step: fault location: the control and the investigation of the sections, the subsection positions and the subsection components are carried out through the inspection equipment and the inspection system, and finally the fault point is determined;
by adopting a gradual elimination method, the fault range is gradually reduced from the whole part to the local part, the complexity of the elimination is reduced, and the fault elimination is performed in a targeted manner by combining the topological structure and the electrical connection relation of the equipment.
Sixth, intelligent decision: intercepting detailed investigation data and fault positioning data, running a decision tree algorithm unit, automatically starting an expert system, and performing intelligent fault decision processing;
seventh step: and (3) fault treatment: according to the fault condition, a specific treatment scheme is formulated, including equipment replacement, parameter adjustment and equipment repair;
and (3) formulating reasonable treatment priority and scheme according to the severity and influence range of the fault, and conforming to the operation rules and maintenance manual of the equipment to ensure the safety and the correctness of the treatment process.
Eighth step: verification and retesting: after the treatment, the treatment scheme is verified, the running condition of the equipment is tested again, and the complete recovery is checked.
Comprehensive equipment tests including functional tests, performance parameter tests and the like are performed, traceability and recording of the verification process are ensured, and subsequent fault analysis and improvement are facilitated.
In the use process, the system has the functions of real-time monitoring and alarming, can timely detect the running condition of equipment, and gives an alarm when abnormal conditions occur; the system supports remote monitoring and management, can access and control the system remotely through a network, acquire the running state in time and carry out necessary adjustment and maintenance; the system has the self-diagnosis and repair capability, can detect and judge faults, and can try to repair by itself or provide a corresponding solution; the system is maintained and updated regularly, including installation of software patches, inspection and cleaning of equipment, etc., to ensure proper operation of the system and to extend the service life of the equipment.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. A transformer substation direct current system fault investigation system is characterized in that: comprises a data acquisition module, a data processing and analyzing module, a fault diagnosis module, a predictive maintenance module, an intelligent decision support module, a fault positioning auxiliary module and a maintenance and test module, wherein,
the data acquisition module comprises a sensor, a detection device and a detection object, wherein the data acquisition module acquires parameter data in a direct current system, the parameter data comprise voltage, current, temperature and grounding current, and the data are sent to the data processing module for processing and storage;
the data processing and analyzing module comprises a data storage device unit, a data processing algorithm unit and a database management system, and is used for receiving the data from the data acquisition module and processing, analyzing and storing the data;
the fault diagnosis module comprises a fault diagnosis algorithm, a fault condition, a topological structure and a connection relation unit, performs fault diagnosis and positioning according to the information provided by the data processing and analyzing module, and helps to determine the position and the reason of the fault by combining the topological structure of the direct current system with the connection relation of equipment;
the predictive maintenance module comprises a machine learning algorithm, a data mining unit and a preprocessing operation library, and utilizes the machine learning and data mining technology to predict and evaluate the equipment state of the direct current system by combining the historical data and the real-time data of the data acquisition module and the result data of the fault diagnosis module so as to discover potential fault signs in advance;
the intelligent decision support module comprises an expert system and a decision tree algorithm unit, integrates the expert system and the decision tree algorithm, provides fault processing suggestions and schemes for operators according to real-time monitoring data of the data acquisition module and fault diagnosis results of the fault diagnosis module, and assists the operators in making decisions;
the fault positioning auxiliary module comprises real-time monitoring equipment and a remote assistance unit, wherein the real-time monitoring equipment comprises a thermal infrared imager and partial discharge detection equipment, and the remote assistance support unit comprises an AR technology and a VR technology.
2. The substation direct current system fault investigation system of claim 1, wherein: the detection object comprises rectifying equipment, a control protection system, a direct current circuit and a battery pack, the fault condition comprises rectifying equipment faults, direct current circuit faults, battery pack faults and control protection system faults, the rectifying equipment comprises a rectifying transformer and a rectifying module, the direct current circuit comprises a direct current bus, a direct current switch and an isolating switch, the control protection system comprises a control protection device and a communication device, and the battery pack comprises a storage battery, a battery cabinet, a fan, a radiator and a filter.
3. The substation direct current system fault investigation system of claim 1, wherein: the wireless sensor network protocol adopted by the data acquisition module is LoRaWAN, and the data acquisition module adopts wireless sensor nodes and a base station to transmit data to the system evaluation module.
4. The substation direct current system fault investigation system of claim 1, wherein: the data processing and analyzing module is an internal communication protocol, the internal communication protocol adopted by the data processing and analyzing module is an internal bus protocol I2C, and the data processing and analyzing module adopts Ethernet to transmit data to the fault recognition and positioning module.
5. The substation direct current system fault investigation system of claim 1, wherein: the fault diagnosis module comprises fault identification and fault positioning, wherein an internal bus protocol Modbus is connected between the fault identification and the fault positioning, and Ethernet data transmission is arranged between the fault diagnosis module and the maintenance and test module.
6. The substation direct current system fault investigation system of claim 1, wherein: the test contents of the maintenance and test module comprise fault discharge result determination, performance test after maintenance and safety test after maintenance.
7. The troubleshooting method of the direct current system troubleshooting system of the transformer substation according to any one of claims 1 to 6, characterized by: the method comprises the following checking steps:
step one, data collection: collecting alarm information, equipment operation state and data information corresponding to the electrical parameters;
second step, preliminary analysis: performing preliminary analysis on the collected data to determine the possible range of occurrence of the problem;
third step, predictive maintenance: intercepting preliminary analysis data, calling a preprocessing operation library in a predictive maintenance module, and under the comparison of initial data, calling the closest preprocessing scheme from the preprocessing operation library to conduct predictive fault detection;
fourth, detailed investigation: obtaining a result of the preliminary analysis, performing on-site checking of equipment, analysis of equipment performance parameters and historical maintenance records, and further determining a fault point;
fifth step, fault location: the control and the investigation of the sections, the subsection positions and the subsection components are carried out through the inspection equipment and the inspection system, and finally the fault point is determined;
sixth, intelligent decision: intercepting detailed investigation data and fault positioning data, running a decision tree algorithm unit, automatically starting an expert system, and performing intelligent fault decision processing;
seventh, fault treatment: specific treatment schemes are formulated in detail according to fault conditions, wherein the specific treatment schemes comprise equipment replacement, parameter adjustment and equipment repair;
eighth step, verifying and retesting: after the treatment, the treatment scheme is verified, the running condition of the equipment is tested again, and the equipment is checked to be completely recovered to be normal.
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