CN113124929A - Transformer substation multi-parameter signal acquisition comprehensive analysis system and method - Google Patents
Transformer substation multi-parameter signal acquisition comprehensive analysis system and method Download PDFInfo
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- G05B19/0428—Safety, monitoring
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract
The invention discloses a multi-parameter signal acquisition and comprehensive analysis system and method for a transformer substation, belonging to the field of monitoring, and the system comprises a voltage current acquisition module, a temperature and humidity acquisition module and an audio acquisition module, wherein the voltage current, the ambient temperature and humidity and the audio signal of equipment are acquired through the voltage current acquisition module, the temperature and humidity acquisition module and the audio acquisition module; the analysis and diagnosis unit integrates the parameter data, acquires real-time data of the parameters and transformer running state information, establishes a database of voltage, current, audio frequency, vibration of the transformer and ambient temperature, humidity and concentration of dissolved gas in oil, acquires a typical data model, extracts characteristic vectors of the parameters according to a spectral clustering algorithm, establishes a characteristic vector database, analyzes and processes the real-time monitoring data, compares the characteristics, can evaluate the working state of the transformer, judges the fault type of the transformer, locates a vibration source of the transformer and outputs a result. The system is helpful for operators to master the actual operation condition of the transformer in real time, and can improve the stability and reliability of the operation of the transformer.
Description
Technical Field
The invention belongs to the field of monitoring, and relates to a system and a method for collecting and comprehensively analyzing multi-parameter signals of a transformer substation.
Background
The power grid is developed in an intelligent mode, and the transformer substation needs to realize unattended operation on the premise of ensuring safe and stable operation, so that stable and reliable operation of the transformer is particularly important. The operating personnel need monitor the running state and the parameter of transformer, in time overhaul, avoid breaking down. If the transformer makes an abnormal sound and no effective measures are taken in time, the economic loss caused by the transformer failure is huge.
During the operation of the transformer, the alternating magnetic flux in the transformer core generates force between the silicon steel sheets of the core, so that a 'buzzing' sound is generated, and the sound is in proportion to the voltage and the current applied to the transformer. In normal operation, the core sound in the transformer should be uniform. When the transformer is in an abnormal operation state, uneven abnormal sounds may occur, such as the sounds are increased more than usual and are even, or the situation that a clack or sand noise, a crackling discharge sound, or a gurgling sound with water boiling exists in the operation process, and the like. And judging the possible abnormal conditions according to the sound when the operator visits, judging whether the safe operation of the transformer is influenced, and stopping the overhaul treatment if necessary.
The factors causing the abnormal sound of the transformer are many, and the common conditions are as follows: the power supply voltage is too high, and the noise is increased and sharp due to over-excitation of the transformer; the transformer load change is large, so that 'Wawa' sound or 'George' sound can be caused, and the sound is irregular but has no noise; overloading causes the transformer to emit a very high and heavy "humming" sound; the loosening of the clamping piece or the screw can cause the transformer to generate strong and uneven noise or the sound of hammering, jingle and blowing, the sound is larger than usual and has obvious noise, but the current meter and the voltmeter have no obvious abnormality; the windings are short-circuited, so that large and uneven crackling or guru boiling water boiling sound is mixed with crackling sound in the transformer oil tank, and huge booming sound is generated when the transformer oil tank is serious; the transformer can generate a 'hissing' sound due to serious pollution or cracks of the porcelain and poor contact of the equipment line card; when partial discharge or poor contact occurs inside the transformer, squeaking or cracking sounds can occur; when the tap changer is not in place, a "chirping" sound may be sounded, etc. The transformer has different sound characteristics due to faults caused by different factors, and by utilizing the characteristic, the sound characteristic information of the monitored equipment is analyzed, so that the working condition of the equipment can be judged in advance, the equipment can be predicted and eliminated before the fault occurs, and the loss caused by abnormal power grid outage due to sudden fault of the power equipment is avoided.
However, the existing device monitoring based on sound characteristics has the defects of single acquired information parameter, high false alarm rate of fault diagnosis, low precision, difficulty in deploying on-site acquisition points of power equipment, high monitoring difficulty, instability and the like.
Disclosure of Invention
The invention aims to overcome the defects of single acquired information parameter, high fault diagnosis false alarm rate, low precision, difficult deployment of on-site acquisition points of power equipment, high monitoring difficulty, instability and the like in equipment monitoring based on sound characteristics in the prior art, and provides a multi-parameter signal acquisition comprehensive analysis system and method for a transformer substation.
In order to achieve the purpose, the invention adopts the following technical scheme to realize the purpose:
a multi-parameter signal acquisition comprehensive analysis system of a transformer substation comprises a data acquisition unit, an analysis and diagnosis unit and a database optimization unit;
the data acquisition unit includes:
the voltage and current acquisition module is used for acquiring voltage and current information of the transformer substation;
the temperature and humidity acquisition module is used for acquiring temperature and humidity information around the transformer substation;
the audio acquisition module is used for acquiring audio information of the transformer substation;
the vibration acquisition module is used for acquiring vibration information of the transformer;
the dissolved gas acquisition module is used for acquiring the concentration information of the dissolved gas in the transformer oil;
the analysis and diagnosis unit is interacted with the data acquisition unit and is used for receiving and processing the information acquired by the data acquisition unit to obtain real-time data of each parameter and the running state information of the transformer; carrying out comprehensive relevance analysis on the obtained real-time data of each parameter and the running state information of the transformer to obtain a typical model, extracting a feature vector of each parameter through a spectral clustering algorithm, establishing a feature vector database, evaluating the working state of the transformer through a feature comparison method, judging the fault type of the transformer, and outputting a result;
and the database optimization unit is used for comparing the actual working condition of the transformer with the output result of the analysis and diagnosis unit and optimizing the characteristic vector database.
Preferably, the vibration acquisition modules are provided with a plurality of vibration acquisition modules which are respectively fixed at different winding positions on the transformer, and acquire the vibration frequency, the vibration amplitude and the vibration position signals of the transformer through the acceleration sensor.
Preferably, the dissolved gas collection module is arranged in the transformer oil, and the dissolved gas concentration information in the transformer oil is obtained through the gas sensor.
Further preferably, the gas sensor includes a hydrogen concentration sensor, a methane concentration sensor, an ethane concentration sensor, an ethylene concentration sensor, and an acetylene concentration sensor.
Preferably, the voltage and current acquisition module is fixed on the periphery of the transformer to be monitored and comprises a PT and a voltage and current acquisition circuit.
Preferably, the audio acquisition module is arranged around the transformer to be monitored and comprises a plurality of audio sensors, and the plurality of audio sensors form an array model around the transformer.
Further preferably, the audio sensor is a digital MEMS sensor.
Preferably, the data acquisition unit comprises a data acquisition terminal arranged on the periphery of the transformer to be monitored, and the data acquisition terminal comprises a display unit, a man-machine interface, a 433M wireless module and a 4G wireless module which are used for data transmission.
Preferably, the analysis and diagnosis unit further comprises a data storage module and a filtering module.
A transformer substation multi-parameter signal acquisition comprehensive analysis method comprises the following steps:
collecting voltage, current, audio and vibration information of a transformer substation, and collecting temperature and humidity information around the transformer substation;
carrying out data processing on the acquired information to obtain real-time data of each parameter and running state information of the transformer;
carrying out comprehensive relevance analysis on the real-time data of each parameter and the running state information of the transformer to obtain a typical model, extracting a feature vector of each parameter through a spectral clustering algorithm, establishing a feature vector database, evaluating the working state of the transformer through a feature comparison method, judging the fault type of the transformer, and outputting a result;
and comparing the actual working condition of the transformer with the output result to optimize the characteristic vector database.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a multi-parameter signal acquisition and comprehensive analysis system for a transformer substation, which is characterized in that voltage and current, ambient temperature and humidity and audio signals of equipment are acquired through a voltage and current acquisition module, a temperature and humidity acquisition module and an audio acquisition module; and then integrating the parameter data, acquiring real-time data of the parameters and running state information of the transformer, establishing a database of voltage, current, audio frequency, vibration of the transformer, the temperature and humidity of the surrounding environment and the concentration of dissolved gas in oil, acquiring a typical data model, extracting characteristic vectors of the parameters according to a spectral clustering algorithm, establishing a characteristic vector database, analyzing and processing the real-time monitoring data, comparing the characteristics, evaluating the working state of the transformer, judging the fault type of the transformer, positioning a vibration source of the transformer and outputting a result. The system can monitor, store and analyze parameter information of the transformer in real time, carry out multi-azimuth real-time monitoring on the running state of equipment, help operators to master the actual running condition of the transformer in real time, and improve the running stability and reliability of the transformer. The method can be widely applied to real-time monitoring of the transformer of the unattended transformer substation.
Furthermore, the vibration acquisition modules are provided with a plurality of vibration acquisition modules which are respectively fixed at different winding positions on the transformer, and the vibration frequency, the vibration amplitude and the vibration position signals are acquired through the acceleration sensor, so that a vibration source can be positioned, the analysis of the fault type of the transformer is assisted, and the fault part is positioned.
The system is further arranged on the periphery of the transformer to be monitored and comprises a plurality of audio sensors, the audio sensors form an array model around the transformer, the audio sensors adopt digital MEMS sensors, and a CPU (Central processing Unit) is arranged in the middle and is responsible for processing data of the 6 sensors to form audio data streams; the audio sensor array is adopted, so that the abnormal sound source can be spatially positioned, and a basis is provided for accurately determining a fault point in space;
further, after evaluation and analysis, the measured data of each parameter is added into a sample database, and a data model is improved and optimized by combining the actual working condition of the transformer, so that a characteristic vector library is optimized. And comparing the actual working condition of the transformer with the evaluation condition, continuously improving the optimization model in the application process, optimizing the characteristic vector library, and establishing a necessary basis for accurate evaluation and judgment.
The invention also discloses a comprehensive analysis method for collecting the multi-parameter signals of the transformer substation, which is carried out based on the system, the method does not rely on single parameter to carry out feature extraction and then evaluation judgment, but carries out multi-parameter and multi-dimension feature identification, reduces the false alarm rate, improves the accuracy rate, can judge the fault type and can carry out accurate fault positioning.
Drawings
FIG. 1 is a schematic diagram of a multi-parameter signal acquisition and comprehensive analysis system of a transformer substation according to the present invention;
FIG. 2 is a schematic diagram of the arrangement of vibration sensors in the multi-parameter signal acquisition comprehensive analysis system of the transformer substation at three different positions of a transformer A, B, C;
FIG. 3 is a schematic diagram of the components of an audio acquisition module in the multi-parameter signal acquisition comprehensive analysis system of the transformer substation;
fig. 4 is a working flow chart of the multi-parameter signal acquisition and comprehensive analysis system of the transformer substation.
Wherein, 1-transformer box body; 2-winding position; 3-an audio sensor; 4-CPU.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings:
example 1
Referring to fig. 1, a multi-parameter signal acquisition and comprehensive analysis system for a transformer substation comprises a data acquisition unit, an analysis and diagnosis unit and a database optimization unit;
the data acquisition unit includes:
the voltage and current acquisition module is used for acquiring voltage and current information of the transformer substation;
the temperature and humidity acquisition module is used for acquiring temperature and humidity information around the transformer substation;
the audio acquisition module is used for acquiring audio information of the transformer substation;
the vibration acquisition module is used for acquiring vibration information of the transformer;
the dissolved gas acquisition module is used for acquiring the concentration information of the dissolved gas in the transformer oil;
the analysis and diagnosis unit is interacted with the data acquisition unit and is used for receiving and processing the information acquired by the data acquisition unit to obtain real-time data of each parameter and the running state information of the transformer; carrying out comprehensive relevance analysis on the obtained real-time data of each parameter and the running state information of the transformer to obtain a typical model, extracting a feature vector of each parameter through a spectral clustering algorithm, establishing a feature vector database, evaluating the working state of the transformer through a feature comparison method, judging the fault type of the transformer, and outputting a result;
and the database optimization unit is used for comparing the actual working condition of the transformer with the output result of the analysis and diagnosis unit and optimizing the characteristic vector database.
Example 2
A multi-parameter signal acquisition and comprehensive analysis system for a transformer substation mainly comprises a voltage and current acquisition module, a temperature and humidity acquisition module, a vibration acquisition module, an audio acquisition module, a dissolved gas acquisition module, an analysis and diagnosis unit and a database optimization unit.
In treating the monitoring area, voltage current acquisition module has been arranged, humiture acquisition module, audio acquisition module, dissolved gas acquisition module, audio acquisition module's sensor array is as shown in fig. 3, vibration acquisition module has been deployed in transformer body A, B, C three position, the deployment position is as shown in fig. 2, gather transformer and surrounding information in real time, then carry out data integration through 433M wireless module with data transfer to data acquisition terminal, after the integration, data acquisition terminal passes through the analysis diagnosis unit in the high in the clouds server of 4G network with data transfer.
The data acquisition terminal can locally display the working state of the transformer and can also give an alarm.
The specific working flow of the cloud server to which the analysis diagnosis unit and the database optimization unit belong is shown in fig. 4, sample data of each parameter is collected, and then a sample database is established; then, establishing a typical data model according to the sample data, and analyzing the internal association between each influence factor and change rule and the noise of the transformer; extracting characteristic vectors of all parameters through a spectral clustering algorithm, and establishing a characteristic vector database; analyzing and processing the real-time monitoring data, comparing the characteristics, diagnosing the running state of the transformer and outputting an evaluation result; and adding the real-time monitoring data into a sample database, comparing the diagnosis result with the actual working condition of the transformer, optimizing and upgrading the data model, and optimizing the characteristic vector database.
Example 3
The contents are the same as those of example 1 except for the following.
The vibration acquisition modules are provided with a plurality of vibration acquisition modules which are respectively fixed at different winding positions on the transformer, and acquire the vibration frequency, the vibration amplitude and the vibration position signals of the transformer through the acceleration sensor. As shown in fig. 2, there are 3 vibration acquisition modules, and acceleration sensors are used to monitor the vibration of the transformer at three different winding positions 2 in the transformer tank 1. And then sending the acquired vibration data to a data acquisition terminal. The vibration acquisition module is arranged on three different windings (winding A, winding B and winding C) of the transformer, and an acceleration sensor is adopted for data acquisition, so that the correlation between a vibration source, vibration amplitude and vibration frequency and abnormal sound emitted by the transformer can be analyzed in an assisting manner, the sound source can be accurately positioned, and the correlation analysis can be performed on the fault type, the fault position and the fault component.
Example 4
The contents are the same as those of example 1 except for the following.
The audio acquisition module is arranged on the periphery of the transformer to be monitored and comprises a plurality of audio sensors, and the plurality of audio sensors form an array model around the transformer. The audio sensor is a digital MEMS sensor. As shown in fig. 3, the audio acquisition module is a circular sensor array formed by 6 audio sensors 3, each sensor has an angle of 60 degrees, the audio sensors are digital MEMS sensors, and a CPU 4 is disposed in the middle of the audio sensors and is responsible for processing data of the 6 audio sensors 3 to form an audio data stream.
Example 5
The contents are the same as those of example 1 except for the following.
The working flow of the analysis and diagnosis unit is shown in fig. 4, the analysis and diagnosis unit can evaluate the actual measurement data in real time, judge the type of the sound source, spatially locate the sound source, judge the fault type of the abnormal sound, locate and analyze the vibration component, and when in use, the actual measurement data can be added into a sample library, so that the mathematical model can be optimized and upgraded, the feature vector library can be optimized, and a basis can be provided for accurate evaluation, diagnosis and location in the later period.
Example 6
In the area to be monitored, all the acquisition modules are deployed at the periphery of the transformer, wherein the voltage current acquisition module acquires voltage current of the transformer, the temperature and humidity acquisition module acquires temperature and humidity of the surrounding environment of the transformer, the vibration acquisition module acquires vibration of the transformer through a plurality of acceleration sensors, the audio acquisition module acquires sound signals through an array consisting of 6 sound sensors, the dissolved gas acquisition module acquires gas dissolved in transformer oil through a gas sensor, the communication transmission network consists of 433M wireless transmission modules and 4G wireless modules, all the acquisition modules transmit field acquisition data to a data acquisition terminal through the 433M wireless modules, the data acquisition terminal transmits the data to an analysis and diagnosis unit through the 4G wireless modules, the analysis and diagnosis unit stores various data according to time, and then performs preprocessing such as filtering on the data, and then, performing time domain analysis on the voltage, the current, the temperature, the humidity, the vibration, the audio signal and the gas concentration, performing spectral clustering algorithm analysis, performing comprehensive relevance analysis on analysis results of all parameters, finally judging the running state of the equipment, and timely notifying operators if abnormal conditions are found.
The invention also discloses a comprehensive analysis method for collecting the multi-parameter signals of the transformer substation, which comprises the following steps:
collecting voltage, current, audio and vibration information of a transformer substation, and collecting temperature and humidity information around the transformer substation;
carrying out data processing on the acquired information to obtain real-time data of each parameter and running state information of the transformer;
carrying out comprehensive relevance analysis on the real-time data of each parameter and the running state information of the transformer to obtain a typical model, extracting a feature vector of each parameter through a spectral clustering algorithm, establishing a feature vector database, evaluating the working state of the transformer through a feature comparison method, judging the fault type of the transformer, and outputting a result;
and comparing the actual working condition of the transformer with the output result to optimize the characteristic vector database.
In summary, the invention is directed to the multi-parameter signal acquisition and comprehensive analysis of the transformer, the data model is obtained by establishing the sample database of each parameter, the characteristic vector of each parameter is extracted by the spectral clustering algorithm, the characteristic vector database is established, the real-time monitoring data is analyzed and processed, and then the characteristic comparison is performed, so that the working state of the transformer can be evaluated, the fault type of the transformer is judged, the vibration source of the transformer is positioned, and the result is output. After evaluation and analysis, the measured data of each parameter is added into a sample database, and a data model is improved and optimized by combining the actual working condition of the transformer, so that a characteristic vector library is optimized. The invention can be widely applied to real-time monitoring of the transformer of the unattended transformer substation.
The above-mentioned contents are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (10)
1. A multi-parameter signal acquisition and comprehensive analysis system of a transformer substation is characterized by comprising a data acquisition unit, an analysis and diagnosis unit and a database optimization unit;
the data acquisition unit includes:
the voltage and current acquisition module is used for acquiring voltage and current information of the transformer substation;
the temperature and humidity acquisition module is used for acquiring temperature and humidity information around the transformer substation;
the audio acquisition module is used for acquiring audio information of the transformer substation;
the vibration acquisition module is used for acquiring vibration information of the transformer;
the dissolved gas acquisition module is used for acquiring the concentration information of the dissolved gas in the transformer oil;
the analysis and diagnosis unit is interacted with the data acquisition unit and is used for receiving and processing the information acquired by the data acquisition unit to obtain real-time data of each parameter and the running state information of the transformer; carrying out comprehensive relevance analysis on the obtained real-time data of each parameter and the running state information of the transformer to obtain a typical model, extracting a feature vector of each parameter through a spectral clustering algorithm, establishing a feature vector database, evaluating the working state of the transformer through a feature comparison method, judging the fault type of the transformer, and outputting a result;
and the database optimization unit is used for comparing the actual working condition of the transformer with the output result of the analysis and diagnosis unit and optimizing the characteristic vector database.
2. The transformer substation multiparameter signal acquisition and comprehensive analysis system according to claim 1, wherein a plurality of vibration acquisition modules are arranged, and are respectively fixed at different winding positions on the transformer, and acquire vibration frequency, vibration amplitude and vibration position signals of the transformer through an acceleration sensor.
3. The substation multiparameter signal acquisition comprehensive analysis system according to claim 1, wherein the dissolved gas acquisition module is arranged in transformer oil, and the dissolved gas concentration information in the transformer oil is acquired through a gas sensor.
4. The substation multiparameter signal acquisition and analysis-by-synthesis system according to claim 3, wherein the gas sensors include a hydrogen concentration sensor, a methane concentration sensor, an ethane concentration sensor, an ethylene concentration sensor, and an acetylene concentration sensor.
5. The substation multiparameter signal acquisition comprehensive analysis system according to claim 1, wherein the voltage and current acquisition module is fixed around the transformer to be monitored and comprises a PT and a voltage and current acquisition circuit.
6. The substation multiparameter signal acquisition and comprehensive analysis system according to claim 1, wherein the audio acquisition modules are arranged around the transformer to be monitored and comprise a plurality of audio sensors, and the plurality of audio sensors form an array model around the transformer.
7. The substation multiparameter signal acquisition and analysis-by-synthesis system according to claim 6, wherein the audio sensor is a digital MEMS sensor.
8. The substation multiparameter signal acquisition comprehensive analysis system according to claim 1, wherein the data acquisition unit comprises data acquisition terminals arranged around the transformer to be monitored, and the data acquisition terminals comprise a display unit, a human-computer interface, and a 433M wireless module and a 4G wireless module for data transmission.
9. The substation multiparameter signal acquisition and analysis-by-synthesis system according to claim 1, wherein the analysis and diagnosis unit further comprises a data storage module and a filtering module.
10. A transformer substation multi-parameter signal acquisition and comprehensive analysis method is characterized by comprising the following steps:
collecting voltage, current, audio and vibration information of a transformer substation, and collecting temperature and humidity information around the transformer substation;
carrying out data processing on the acquired information to obtain real-time data of each parameter and running state information of the transformer;
carrying out comprehensive relevance analysis on the real-time data of each parameter and the running state information of the transformer to obtain a typical model, extracting a feature vector of each parameter through a spectral clustering algorithm, establishing a feature vector database, evaluating the working state of the transformer through a feature comparison method, judging the fault type of the transformer, and outputting a result;
and comparing the actual working condition of the transformer with the output result to optimize the characteristic vector database.
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| CN114091984A (en) * | 2022-01-21 | 2022-02-25 | 北京智盟信通科技有限公司 | Power transformer operation state evaluation method and equipment |
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| CN117538686A (en) * | 2023-12-20 | 2024-02-09 | 四川易信达电气有限公司 | Power supply equipment fault detection method and system |
| CN117828512A (en) * | 2024-03-04 | 2024-04-05 | 天津通安变压器有限公司 | Rapid evaluation and prediction method for operation risk of oil immersed transformer |
| CN118035943A (en) * | 2024-04-12 | 2024-05-14 | 国网山东省电力公司淄博供电公司 | Transformer state monitoring method, system, electronic equipment and storage medium |
| CN118362943A (en) * | 2024-06-19 | 2024-07-19 | 国网山东省电力公司聊城供电公司 | Transformer monitoring device and method based on non-electric quantity comprehensive characteristic information |
| CN118362943B (en) * | 2024-06-19 | 2024-10-11 | 国网山东省电力公司聊城供电公司 | Transformer monitoring device and method based on non-electric quantity comprehensive characteristic information |
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