Vibration data fusion and image recognition-based transformer fault diagnosis method
A transformer fault and vibration data technology, applied in character and pattern recognition, vibration measurement, vibration measurement in solids, etc., can solve problems such as inability to monitor and diagnose transformers, affect the safe and stable operation of the power grid, and reduce the ability to withstand short-circuit shocks, etc., to achieve High-precision automatic fault diagnosis, easy implementation and promotion, and simple methods
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[0017] The inventive method step is as follows:
[0018] 1. Data collection. The invention collects vibration data of multiple vibration measuring points under various typical fault states of transformers, such as iron core vibration caused by magnetostriction, iron core vibration caused by electromagnetic attraction, winding looseness, cooling device vibration and other fault types. For any typical fault, a sampling process of any vibration measuring point is composed of several sampling time points.
[0019] 2. Fault modeling. Extract the eigenvalues of the collected vibration data under various typical fault states of the transformer to form an eigenvalue matrix. matrix database.
[0020] 3. Diagnosis method based on image recognition technology. suppose The eigenvalue matrix of It is the sample matrix of any typical fault of the transformer, which reflects the process change law of this typical fault, as shown in formula (1):
[0021] (1)...
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