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Signal Recognition Method of Power Cable Oscillating Wave Partial Discharge Detection Based on Support Vector Machine

Oscillating wave partial discharge detection technology has been widely used because of its powerful applicability. However, the detection process will produce short duration, burst, non-stationary impulse noise, whose characteristics are similar to partial discharge signals, and it is difficult to denoise by traditional methods such as filtering. In accordance with the above problems, this paper presents a method of recognition and noise reduction of oscillating partial discharge signal based on support vector machine. A classifier of noise pulse and partial discharge signal is established to eliminate impulse noise in partial discharge signal. Aiming at the difference of time-frequency characteristics between oscillating partial discharge signal and impulse noise, support vector machine classifier is used to identify partial discharge signal and impulse noise. It can overcome the defect that the traditional filtering method is difficult to suppress impulse noise. The experimental results show that, compared with the traditional empirical threshold method, the accuracy of partial discharge defect location is improved by more than 7.5%, which can effectively improve the accuracy of partial discharge location detection.