A Cyclic Progressive Partial Discharge Discrimination Method
A partial discharge and discrimination method technology, applied in the field of cyclic progressive partial discharge discrimination, can solve the problems of misjudging noise as partial discharge, misjudgment and false alarm, etc., and achieves the effect of low misjudgment rate, accurate judgment and abundant samples
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Embodiment approach 1
[0058] like Figure 7 As shown, the background data processing and analysis center MS starts to discriminate after receiving the detection signal, and reads the detection data into the logic gate f 1 -q-n 1 -t 1 Eigenvalue discrimination, preliminary discrimination threshold setting: f 1 (1~5MHz), q(50~80pC), n 1 (20~30pps), t 1 (3~5min), preliminarily determine whether the detected signal is PD or noise. If the eigenvalues f, q, n, and t of the detected signal all meet the set threshold, it is determined as PD, and the first neural network judgment mechanism is entered; Otherwise, it is judged as the end judgment of noise.
[0059] The first neural network discrimination mechanism: discriminate the three-dimensional map feature of the detected signal, give a partial discharge similarity percentage value, and then judge whether the detected signal is partial discharge or noise. If the percentage value of the detected signal output is greater than or equal to 90% For pa...
Embodiment approach 2
[0067] like Figure 8 As shown, the neural network can discriminate more than two types of PD and Noise by discriminating signal types. The output layer contains 6 PD types and 3 Noise types, a total of 9 type data parameter libraries, which are:
[0068] PD1—insulation hole partial discharge signal;
[0069] PD2—insulation interface creepage partial discharge signal;
[0070] PD3—Insulation impurity partial discharge signal;
[0071] PD4—interface gap partial discharge signal;
[0072]PD5—Inner conductor raised partial discharge signal (tip discharge);
[0073] PD6—outer conductor raised partial discharge signal (tip discharge);
[0074] Noise1—single-group, double-group, three-group, multi-group corona noise;
[0075] Noise2—vertical building-like, horizontal pie-like double-cluster noise;
[0076] Noise3—Noisy, no phase characteristic noise.
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