Transformer abnormal state detection method based on multi-measuring-point vibration signals

Abstract

The invention discloses a transformer abnormal state detection method based on multi-measuring-point vibration signals. The method comprises the following steps: uniformly arranging a plurality of vibration sensors on the surface of a transformer oil tank, extracting a time domain feature vector of a vibration signal of each vibration sensor by adopting fast Fourier decomposition, classifying feature vectors of each vibration sensor in different time periods by adopting a k-means clustering algorithm, and finally obtaining k clustering centers and corresponding fluctuation ranges; determiningconfidence coefficient functions of the vibration signals of the vibration sensors in different states; and taking the operation state corresponding to the maximum value of the confidence function asa diagnosis result of the transformer state. According to the transformer abnormal state detection method based on the multi-measuring-point vibration signals, the vibration signals of the multiple measuring points on the surface of the oil tank can be comprehensively analyzed, and comprehensive evaluation of the running state of the transformer is achieved.

Description

technical field [0001] The invention relates to the technical field of transformer fault detection, in particular to a transformer abnormal state detection method based on vibration signals of multiple measuring points. Background technique [0002] For transformer equipment operating on site, due to the complex operating environment and the influence of factors such as load changes, there may be various degrees of mechanical deformation faults in the core and windings inside the transformer after long-term operation. It is not sensitive to mechanical faults, but the vibration signal is very sensitive to mechanical deformation, which is suitable for the detection of mechanical deformation faults of transformers. [0003] The vibration generated by the transformer winding and the iron core propagates to the surface of the oil tank through the two propagation paths of fasteners and insulating oil, and only the component perpendicular to the direction of the oil tank wall can b...

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Problems solved by technology

These transformer fault detection methods have the following shortcomings: the analysis only for a small number of measuring points ignores the different fault information contained in the vibration signals at different positions on the surface of the transformer oil tank due to the different propagation paths, and the analysis only for a small number of measuring points at local positions is difficult to comprehensively Reflect the overall health status of the transformer; the electromagnetic simulation method using finite element electromagnetic simulation has too high requirements on the parameters of the actual model, and it is necessary to accurately know the material characteristic curve of each component of the transformer, the magnetization curve of the silicon steel sheet, and the operating current and voltage. Difficult to achieve in substation operation and maintenance

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