Gas insulated substation (GIS) partial discharge online monitoring system and fault mode identifying method thereof
A partial discharge monitoring and partial discharge technology, which is applied in the direction of testing dielectric strength, can solve the problems of increasing the uncertainty of final fault diagnosis, low recognition rate, and no pattern recognition function, etc., and achieves simple structure, improved recognition accuracy, and training The effect of shortening the time
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Embodiment 1
[0074] Embodiment 1: In the specific implementation of the present invention, after the characteristic spectrogram is generated, the statistical operator is calculated, and the simplified statistical operator of this embodiment is 7, which are respectively the skewness Sk, the prominence Ku, and the number of local peaks Pe, discharge asymmetry Q, phase asymmetry The cross-correlation factor cc and phase median value μ are obtained through general formulas. Let the seven statistical operators be a 1 ,a 2 …a 7 , let T be the decision table, the condition attributes are 7 statistical operators; the decision attributes are 4 types of faults, numbered 1, 2, 3, 4; the number of sample sets is 9, let it be x 1 ,x 2 ,...,x 9 ; The decision table T is as follows:
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[0077] According to the steps mentioned earlier, the decision table is reduced.
[0078] The principle of reduction is, firstly, after the feature spectrum is generated, the statistical opera...
Embodiment 2
[0095] Embodiment 2: In this embodiment, GIS partial discharge is monitored online and the collected data is processed through the online monitoring software system to obtain 31 sample data of characteristic values as input, and the five types of defects are identified by pattern classification, and the input The sample data is fuzzified, knowledge rule extraction and reduction are preprocessed as the output of the neural network, corresponding to five types of faults. Corresponding to five faults: fixed protrusions on the busbar, fixed protrusions on the inner wall, particles on the surface of the pot insulator, bubbles inside the pot insulator, and free metal particles, the expected outputs are A (1 0 0 0 0) , B (0 1 0 00), C (0 0 1 0 0), D (0 0 0 1 0), E (0 0 0 0 1). The output results are shown in Table 1.
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[0097] Table 1
[0098] The recognition results show that the system has realized the long-term on-line monitoring function of GIS partial discharge, a...
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