Internal discharge mode recognition method and fault diagnosis system for transformer

Abstract

The invention provides an internal discharge mode recognition method for a transformer, which is characterized in that: a singularity index of a signal waveform is extracted from a discharge acoustical signal of a transformer with a known internal fault; singularity indexes of signal waveforms corresponding to various discharge modes are collected, and an acoustical signal feature library for various discharge modes is established; the waveform of a discharge acoustical signal of the monitored transformer is monitored and obtained, and the singularity index of the signal waveform is extracted; the singularity index of the signal waveform of the discharge acoustical signal of the monitored transformer is compared with the acoustical signal feature library, and if the singularity index of the signal waveform of the discharge acoustical signal of the monitored transformer is the same as the singularity index in the feature library, the corresponding discharge mode is determined. The invention further provides an internal discharge fault diagnosis system for the transformer, which is based on the method. According to the method, the internal discharge acoustical signal of the transformer is precisely and stably monitored, the internal discharge mode recognition is performed accurately, and a fault can be found in time through analysis and process of the monitored acoustical signal.

Description

technical field [0001] The invention relates to the technical field of transformers, in particular to a transformer internal discharge pattern recognition method based on discharge acoustic signal analysis and a transformer internal fault diagnosis system. Background technique [0002] Power transformers play an extremely important role in the continuous and stable transmission of electric energy, and their reliable operation is directly related to the insulation condition. The internal discharge of the transformer is a common fault of the transformer. The internal discharge of the transformer will cause the insulation to deteriorate and the internal components to work abnormally, which will cause the transformer to break away from the normal operation state, and even pose a threat to the surrounding power equipment, resulting in a series of serial accidents. [0003] Internal discharge faults of the transformer include arcing caused by melting of lead wire joints, discharge...

AI Technical Summary

Problems solved by technology

On-line monitoring mainly includes dielectric loss measurement, oil chromatographic monitoring, ultrasonic monitoring and other methods. These methods have good real-time performance, but the macroscopic characteristic quantities reflecting insulation defects are too small, and are easily interfered by on-site electric and magnetic fields, which seriously affect the measurement accuracy. and the accuracy of monitoring results; offline detection mainly includes oil chromatography detection, no-load loss, short-circuit loss and withstand voltage tests. These methods can accurately find problems, but the detection period is long and does not have real-time performance. There is no guarantee that the transformer can operate safely between two offline tests

[0005] In summary, the traditional transformer internal discharge test method is difficult to take into account both the real-time performance of the monitoring process and the accuracy of the monitoring results, and it is difficult to quickly identify the internal discharge mode of the transformer.

Various tests are only isolated test methods, and it is difficult to form an effective transformer fault diagnosis system

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