Transformer winding fault diagnosis method based on atomic sparse decomposition
A technology of atomic sparse decomposition and transformer windings, applied in instruments, molecular computers, measurement of electrical variables, etc., can solve the problems of deviation of diagnosis results, recognition ability is easily affected by its own parameters, poor convergence, etc., to achieve the effect of improving accuracy
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[0078] Will test sample T 2 As the input, the fault type of the transformer winding is used as the output, and the transformer winding fault diagnosis model test sample T based on atomic sparse decomposition 2 Part of the data is shown in Table 1. The fault diagnosis result of the transformer winding is shown in Table 2.
[0079] Table 1 Training sample T 2 part of data
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[0081] Table 2 Diagnosis results
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[0083] According to the data in Table 2, when the number of training steps is 1000, training data 1 and 2 are divided into one category, 3, 4, 5, 6, 7, and 8 are divided into another category, and the GSO-SOM network performs Preliminary classification. When the number of training steps is 2500, 1 and 2, 3 and 4, 5 and 6, 7 and 8 are classified into the same category. At this time, the GSO-SOM network further divides the data, which can be used for transformer winding faults. Types are correctly classified. From the test results of the GSO-SOM network, the GSO-...
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