CN107228913B - State diagnosis system for fault type of transformer - Google Patents
State diagnosis system for fault type of transformer Download PDFInfo
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- CN107228913B CN107228913B CN201710434086.2A CN201710434086A CN107228913B CN 107228913 B CN107228913 B CN 107228913B CN 201710434086 A CN201710434086 A CN 201710434086A CN 107228913 B CN107228913 B CN 107228913B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/62—Detectors specially adapted therefor
- G01N30/64—Electrical detectors
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
- G01R31/1263—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation
- G01R31/1281—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation of liquids or gases
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- Housings And Mounting Of Transformers (AREA)
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Abstract
The invention relates to the technical field of power equipment state monitoring and fault diagnosis, in particular to a state diagnosis system of a transformer fault type, which comprises an oil sample acquisition module, an oil-gas separation module, a gas detection module, a data processing module and a data transmission module; the invention successfully realizes the rapid, accurate and real-time detection of the dissolved gas component and concentration in the insulating oil of the transformer, avoids the defect of lacking long-term stable and reliable monitoring means in the operation and maintenance of the transformer, and provides reliable data for on-line evaluation and analysis of the running state and the residual life of the transformer; the method has the advantages that the sampling search algorithm based on the Euclidean distance is introduced into fault type identification, the problems of ambiguity and applicability of dissolved gas data in insulating oil are overcome, the accuracy and timeliness of fault identification are improved, and the aim of comprehensively optimizing risk, efficiency and cost in power safety production is fulfilled.
Description
Technical Field
The invention relates to the technical field of power equipment state monitoring and fault diagnosis, in particular to a state diagnosis system of a transformer fault type.
Background
The transformer is often an oil-filled transformer, with insulating oil as the medium for insulation and heat dissipation. In actual operation, the transformer insulating oil and the solid insulating material are gradually aged, decomposed and generated into characteristic gases dissolved in the oil under the action of electricity and heat, when the latent defects exist, the generation speed of the gases and the quantity dissolved in the insulating oil are increased, and the composition and the content of fault gases are closely related to the type and the severity of equipment faults. Therefore, monitoring the dissolved gas condition of the transformer insulating oil is one of important means for monitoring the operation of the transformer, and can help to discover early insulation defects in the transformer, and through timely fault diagnosis and state evaluation, specific treatment measures are adopted to avoid malignant development of the transformer. However, due to the problems of complex actual faults and operation environment of equipment, incomplete fault type discrimination knowledge, fuzzy fault key information and the like, the existing monitoring device for the dissolved gas state in the insulating oil of the transformer mainly realizes the detection of characteristic gas in the insulating oil and does not have the capability of fault type diagnosis.
Disclosure of Invention
In order to solve the problems, the invention provides a state diagnosis system for a transformer fault type, which comprises the following specific technical scheme:
the state diagnosis system of the transformer fault type comprises an oil sample acquisition module, an oil-gas separation module, a gas detection module, a data processing module and a data transmission module; the oil sample collection module is used for collecting insulating oil in the transformer body and inputting the collected insulating oil in the transformer body to the oil-gas separation module; the oil-gas separation module is used for separating the insulating oil in the transformer body acquired by the oil sample acquisition module and the mixed gas dissolved in the insulating oil and inputting the separated mixed gas into the gas separation module; the gas separation module is used for separating each gas component of the mixed gas separated from the oil-gas separation module and inputting each separated gas component into the gas detection module; the gas detection module is used for detecting the concentration of each gas component input from the gas separation module and converting the concentration of each gas component into an electric signal to be input to the data processing module; the data processing module is used for collecting, processing and storing the data of the concentration of each gas component detected by the gas detection module, diagnosing the fault type of the transformer, and inputting the concentration data of each gas component and the diagnosis result of the fault type of the transformer to the data transmission module; the data transmission module is used for uploading the concentration data of each gas component and the fault type diagnosis result of the transformer input by the data processing module to the state monitoring and evaluating center; the oil sample collection module, the oil-gas separation module, the gas detection module, the data processing module and the data transmission module are sequentially connected.
Further, the oil sample collection module comprises an oil inlet pipe, an oil return pipe, 2 oil valves and an air booster pump; one end of the oil inlet pipe is connected with an oil injection valve of the transformer, the oil inlet pipe is provided with an oil valve, and the other end of the oil inlet pipe is connected with an air booster pump; one end of the oil return pipe is connected with an oil discharge valve of the transformer, the oil return pipe is provided with an oil valve, and the other end of the oil return pipe is connected with an air booster pump.
Further, the oil-gas separation module comprises a variable diameter piston pump.
Further, the gas separation module comprises 2 composite gas chromatographic columns.
Further, the gas detection module includes a resistive semiconductor gas sensor.
Further, the data processing module comprises an A/D conversion chip and a microcontroller.
Further, the data transmission module comprises a communication board card.
Further, the data processing module adopts a sample retrieval algorithm to diagnose the fault type of the transformer, and comprises the following steps:
(1) Establishing a fault sample library
Collecting fault samples dissolved in transformer insulating oil when more than 500 transformers truly fail, and building a fault sample library after training; setting n fault types after training; the method is characterized in that all mixed gas dissolved in the transformer insulating oil is taken as characteristic gas when the transformer truly fails,setting w total characteristic gases in the fault sample library; x is a fault sample matrix, then the fault sample matrix；/>
(2) Variable clustering analysis
Calculating the generic degree of the characteristic gas in the mixed gas dissolved in the actual measurement transformer insulating oil and the fault sample in the fault sample library so as to diagnose the fault type most matched with the transformer; the fault samples in the fault sample library comprise transformer insulating oil overheat, partial discharge in transformer insulating oil paper, spark discharge in transformer insulating oil, high-energy discharge in transformer insulating oil and insulating paper; the method comprises the following steps:
1) Calculation of Euclidean distance of characteristic gas
Taking the characteristic gas dissolved in the measured transformer insulating oil as a characteristic index, setting the number of the characteristic indexes as m, and setting the measured characteristic index vector as Y, then measuring the characteristic index vector，/>The method comprises the steps of carrying out a first treatment on the surface of the The Euclidean distance is used for describing the distance between the actually measured characteristic index vector Y and each row vector of the fault sample matrix X respectively, and the calculation formula is as follows:
；/>
where i is the row number of the fault sample matrix X,j is the characteristic gas number, +.>；
2) Calculating a degree of similarity
Is provided withFor actually measuring the degree of similarity of the faults of the transformer and the fault types in the fault sample library, the following is +.>The calculation formula of (2) is as follows:
；/>
comparing the measured transformer faults with the generic degree of each fault type in the fault sample library, and finding the maximum value of the generic degreeAnd the actual measured transformer faults are most matched with the fault types represented by the row vectors of the ith row corresponding to the fault sample matrix X, so that the most matched fault types in the actual measured transformer faults and the fault sample library are diagnosed.
Further, the oil valve is a flange type oil valve.
Further, the surfaces of the oil inlet pipe and the oil return pipe are respectively covered with the heat tracing belt.
The invention successfully realizes the rapid, accurate and real-time detection of the dissolved gas component and concentration in the insulating oil of the transformer, avoids the defect of lacking long-term stable and reliable monitoring means in the operation and maintenance of the transformer, and provides reliable data for on-line evaluation and analysis of the running state and the residual life of the transformer. The method has the advantages that the sampling search algorithm based on the Euclidean distance is introduced into fault type identification, the problems of ambiguity and applicability of dissolved gas data in insulating oil are overcome, the accuracy and timeliness of fault identification are improved, and the aim of comprehensively optimizing risk, efficiency and cost in power safety production is fulfilled.
Drawings
Fig. 1 is a schematic structural view of the present invention.
Detailed Description
For a better understanding of the present invention, reference is made to the following description of the invention, taken in conjunction with the accompanying drawings and specific examples:
the state diagnosis system of the transformer fault type comprises an oil sample acquisition module, an oil-gas separation module, a gas detection module, a data processing module and a data transmission module; the oil sample collection module is used for collecting insulating oil in the transformer body and inputting the collected insulating oil in the transformer body to the oil-gas separation module; the oil-gas separation module is used for separating the insulating oil in the transformer body acquired by the oil sample acquisition module and the mixed gas dissolved in the insulating oil and inputting the separated mixed gas into the gas separation module; the gas separation module is used for separating each gas component of the mixed gas separated from the oil-gas separation module and inputting each separated gas component into the gas detection module; the gas detection module is used for detecting the concentration of each gas component input from the gas separation module and converting the concentration of each gas component into an electric signal to be input to the data processing module; the data processing module is used for collecting, processing and storing the data of the concentration of each gas component detected by the gas detection module, diagnosing the fault type of the transformer, and inputting the concentration data of each gas component and the diagnosis result of the fault type of the transformer to the data transmission module; the data transmission module is used for uploading the concentration data of each gas component and the fault type diagnosis result of the transformer input by the data processing module to the state monitoring and evaluating center; the oil sample collection module, the oil-gas separation module, the gas detection module, the data processing module and the data transmission module are sequentially connected.
The oil sample acquisition module comprises an oil inlet pipe, an oil return pipe, 2 oil valves and an air booster pump; one end of the oil inlet pipe is connected with an oil injection valve of the power transformer, the oil inlet pipe is provided with an oil valve, and the other end of the oil inlet pipe is connected with an air booster pump; one end of the oil return pipe is connected with an oil discharge valve of the power transformer, the oil return pipe is provided with an oil valve, and the other end of the oil return pipe is connected with an air booster pump; the oil valve is a flange type oil valve, the oil inlet pipe and the oil return pipe adopt copper pipes with the diameter of 8 mm and the density of 8.96 g/cc, the surfaces of the oil inlet pipe and the oil return pipe are respectively covered with a heat tracing belt, the air booster pump adopts a miniature reciprocating air booster pump, and the oil flow speed is less than 0.5m/s.
The oil-gas separation module comprises a variable diameter piston pump, the oil-gas separation module adopts a vacuumizing and degassing method to perform oil-gas separation, and adopts the variable diameter piston pump to repeatedly move up and down, expand capacity and degas for multiple times, compress and collect gas, so that dissolved gas in insulating oil is rapidly separated out, the degassing efficiency is that more than 95% of dissolved gas in the oil can be separated within 15 minutes, and the volume of an oil-gas chamber is 350 milliliters.
The gas separation module comprises composite gas chromatographic columns, and can automatically separate H2, CO2, CH4, C2H6, C2H4, C2H2 and other gas components in the mixed gas, wherein the number of the composite gas chromatographic columns is 2, and the gas chromatographic columns are in line with the adoption of GC series.
The gas detection module includes a resistive semiconductor gas sensor having a measurement accuracy such that the repeatability of the measurement is less than 10% when the dissolved gas content in the insulating oil is greater than 10 microliters per liter, and the measurement repeatability is less than 20% when the dissolved gas content in the insulating oil is not greater than 10 microliters per liter.
The data processing module comprises an A/D conversion chip and a microcontroller, wherein the A/D conversion chip adopts a TM7707 double-channel A/D conversion chip of an ADC series with more than 24 bits; the microcontroller adopts an M058S series microcontroller.
The data transmission module comprises a communication board card; the communication board card adopts an Intel 9301CT communication board card.
The data processing module adopts a sample retrieval algorithm to diagnose the fault type of the transformer, and comprises the following steps:
collecting fault samples dissolved in transformer insulating oil when more than 500 transformers truly fail, and building a fault sample library after training; setting n fault types after training; taking all the mixed gas dissolved in the transformer insulating oil as characteristic gas when the transformer truly fails, and setting all the characteristic gas in a failure sample library as w; x is a fault sample matrix, then the fault sample matrix
；/>
For example, collecting mixed gas samples dissolved in transformer insulating oil when 700 transformers truly fail, and building a failure sample library after training; wherein 383 transformer fault samples belong to overheat of the transformer, 317 transformer fault samples belong to discharge of the transformer, 6 fault types exist after training, as shown in Table 1, all mixed gas dissolved in transformer insulating oil during actual fault of the transformer is taken as characteristic gas, and the characteristic gas is H 2 、CO、CO 2 、CH 4 、C 2 H 6 、C 2 H 4 、C 2 H 2 All characteristic gases in the fault sample library are 7; x is a fault sample matrix, then the fault sample matrix
；/>
Table 1 transformer fault sample library
(2) Variable clustering analysis
Calculating the generic degree of the characteristic gas in the mixed gas dissolved in the actual measurement transformer insulating oil and the fault sample in the fault sample library so as to diagnose the fault type most matched with the transformer; the fault samples in the fault sample library comprise transformer insulating oil overheat, partial discharge in transformer insulating oil paper, spark discharge in transformer insulating oil, high-energy discharge in transformer insulating oil and insulating paper; the method comprises the following steps:
1) Calculation of Euclidean distance of characteristic gas
Taking the characteristic gas dissolved in the measured transformer insulating oil as a characteristic index, setting the number of the characteristic indexes as m, and setting the measured characteristic index vector as Y, then measuring the characteristic index vector，/>The method comprises the steps of carrying out a first treatment on the surface of the The Euclidean distance is used for describing the distance between the actually measured characteristic index vector Y and each row vector of the fault sample matrix X respectively, and the calculation formula is as follows:
；/>
where i is the row number of the fault sample matrix X,j is the characteristic gas number, +.>；
2) Calculating a degree of similarity
Is provided withFor actually measuring the degree of similarity of the faults of the transformer and the fault types in the fault sample library, the following is +.>The calculation formula of (2) is as follows:
；/>
comparing the measured transformer faults with the generic degree of each fault type in the fault sample library, and finding the maximum value of the generic degreeAnd the actual measured transformer faults are most matched with the fault types represented by the row vectors of the ith row corresponding to the fault sample matrix X, so that the most matched fault types in the actual measured transformer faults and the fault sample library are diagnosed.
And respectively connecting an oil inlet pipe and an oil return pipe of the oil sample acquisition module to an oil injection valve and an oil discharge valve of the transformer, and transmitting the acquired transformer insulating oil to the oil-gas separation module for degassing. The oil-gas separation module separates and collects the mixed gas dissolved in the transformer insulating oil by adopting a vacuum degassing mode, and inputs the mixed gas into the gas separation module for separation by carrier gas of more than 0.2 megapascals. The gas separation module separates H through a composite gas chromatographic column 2 、CO、CO 2 、CH 4 、C 2 H 6 、C 2 H 4 、C 2 H 2 And (3) waiting for each component gas, and sending each component gas to a gas detection module for detection. The gas detection module sequentially detects each separated component gas through the resistance type semiconductor gas sensor, and inputs concentration signals of each component gas into the data processing module for conversion and storage, the data processing module converts and stores digital signals proportional to the concentration of each component gas, the fault type of the transformer is diagnosed based on a sample retrieval algorithm, and the digital signals and diagnosis results are input into the data transmission module. The data transmission module adopts an Intel 9301CT communication board card to communicate with the electric powerThe comprehensive data network transmits the digital signals and the diagnosis results to the state monitoring and evaluation center for monitoring, analyzing and calling by equipment operation and maintenance personnel. Six common types of equipment failure were identified by analysis of dissolved gas in the insulating oil of the transformer: the internal state of the transformer can be judged, the severity degree and the development speed of abnormality are tracked, and corresponding fault checking treatment measures are adopted. By analyzing the gas dissolved in the insulating oil of the transformer, the transformer insulating oil and the solid insulating material can be aged and decomposed into a small amount of combustible gas under the action of heat and electricity under the normal operation state of equipment, but the gas production rate is slower; when the latent abnormality occurs, the severity and the development speed of the abnormality in the equipment can be tracked and judged by virtue of the characteristic gas content in the insulating oil, and the gas content and the gas production rate at the moment are more visual for judging the existence, severity and development trend of the fault.
The present invention is not limited to the specific embodiments described above, but is to be construed as being limited to the preferred embodiments of the present invention, and any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention are intended to be included in the scope of the present invention.
Claims (9)
1. A condition diagnosing system of a transformer fault type, characterized by: the device comprises an oil sample acquisition module, an oil-gas separation module, a gas detection module, a data processing module and a data transmission module; the oil sample collection module is used for collecting insulating oil in the transformer body and inputting the collected insulating oil in the transformer body to the oil-gas separation module; the oil-gas separation module is used for separating the insulating oil in the transformer body acquired by the oil sample acquisition module and the mixed gas dissolved in the insulating oil and inputting the separated mixed gas into the gas separation module; the gas separation module is used for separating each gas group of the mixed gas separated from the oil-gas separation moduleInputting each separated gas component into a gas detection module; the gas detection module is used for detecting the concentration of each gas component input from the gas separation module and converting the concentration of each gas component into an electric signal to be input to the data processing module; the data processing module is used for collecting, processing and storing the data of the concentration of each gas component detected by the gas detection module, diagnosing the fault type of the transformer, and inputting the concentration data of each gas component and the diagnosis result of the fault type of the transformer to the data transmission module; the data transmission module is used for uploading the concentration data of each gas component and the fault type diagnosis result of the transformer input by the data processing module to the state monitoring and evaluating center; the oil sample acquisition module, the oil-gas separation module, the gas detection module, the data processing module and the data transmission module are sequentially connected; the gas component comprises: h 2 ，C 2 H 2 ，C 2 H 4 ，CO，CH 4 ，C 2 H 6 ，CO 2 ；
The data processing module adopts a sample retrieval algorithm to diagnose the fault type of the transformer, and comprises the following steps:
(1) Establishing a fault sample library
Collecting fault samples dissolved in transformer insulating oil when more than 500 transformers truly fail, and building a fault sample library after training; setting n fault types after training; taking all the mixed gas dissolved in the transformer insulating oil as characteristic gas when the transformer truly fails, and setting all the characteristic gas in a failure sample library as w; x is a fault sample matrix, then the fault sample matrix
(2) Variable clustering analysis
Calculating the generic degree of the characteristic gas in the mixed gas dissolved in the actual measurement transformer insulating oil and the fault sample in the fault sample library so as to diagnose the fault type most matched with the transformer; the fault samples in the fault sample library comprise transformer insulating oil overheat, partial discharge in transformer insulating oil paper, spark discharge in transformer insulating oil, high-energy discharge in transformer insulating oil and insulating paper; the method comprises the following steps:
1) Calculation of Euclidean distance of characteristic gas
Taking the characteristic gas dissolved in the measured transformer insulating oil as a characteristic index, setting the number of the characteristic indexes as m and setting the measured characteristic index vector as Y, then measuring the characteristic index vector Y= (Y) 1 …y m ) M is less than or equal to w; the Euclidean distance is used for describing the distance between the actually measured characteristic index vector Y and each row vector of the fault sample matrix X respectively, and the calculation formula is as follows:
wherein i is the line number of the fault sample matrix X, i epsilon (1, n), j is the characteristic gas number, j epsilon (1, w);
2) Calculating a degree of similarity
Set S i For actually measuring the generic degree of each fault type in the transformer fault and fault sample library, S i The calculation formula of (2) is as follows:
comparing the measured transformer faults with the generic degree of each fault type in the fault sample library, and finding out the maximum value Max { S } of the generic degree i And if so, the fault type of the actual measured transformer is most matched with the fault type represented by the row vector of the ith row corresponding to the fault sample matrix X, so that the fault type of the actual measured transformer is diagnosed to be most matched with the fault type in the fault sample library.
2. A status diagnostic system of the type of transformer fault as claimed in claim 1 wherein: the oil sample collecting module comprises an oil inlet pipe, an oil return pipe, 2 oil valves and an air booster pump; one end of the oil inlet pipe is connected with an oil injection valve of the transformer, the oil inlet pipe is provided with an oil valve, and the other end of the oil inlet pipe is connected with an air booster pump; one end of the oil return pipe is connected with an oil discharge valve of the transformer, the oil return pipe is provided with an oil valve, and the other end of the oil return pipe is connected with an air booster pump.
3. A status diagnostic system of the type of transformer fault as claimed in claim 1 wherein: the oil-gas separation module comprises a reducing piston pump.
4. A status diagnostic system of the type of transformer fault as claimed in claim 1 wherein: the gas separation module comprises 2 composite gas chromatographic columns.
5. A status diagnostic system of the type of transformer fault as claimed in claim 1 wherein: the gas detection module includes a resistive semiconductor gas sensor.
6. A status diagnostic system of the type of transformer fault as claimed in claim 1 wherein: the data processing module comprises an A/D conversion chip and a microcontroller.
7. A status diagnostic system of the type of transformer fault as claimed in claim 1 wherein: the data transmission module comprises a communication board card.
8. A status diagnostic system of the type of transformer fault as claimed in claim 2 wherein: the oil valve is a flange type oil valve.
9. A status diagnostic system of the type of transformer fault as claimed in claim 2 wherein: the surface of the oil inlet pipe and the surface of the oil return pipe are respectively covered with the heat tracing belt.
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