System and method of partial discharge detection using ultrasound based on optimized deep learning approach

A method for classifying Partial Discharge (PD) in an electrical equipment, comprising:

• detecting, by an acoustic emission sensor, a mechanical wave produced by an electrical discharge event and converting the mechanical wave into an audio signal;
• determining, by a signal preprocessing unit, a waveform of the audio signal and converting the determined waveform into a waveform image, wherein the converting includes performing a Short-Time Fourier Transform (STFT) on the audio signal to preserve time information and further to convert the audio signal into a spectrogram as the waveform image;
• predicting, by a processing circuitry configured with a Convolution Neural Network (CNN) that takes as input the waveform image, a fault class among four different PD types which are an arcing, a corona discharge, a tracking, a looseness, as well as a healthy equipment;
• and
• outputting, by an output device, an indication of the fault class of the electrical equipment.

A non-transitory computer-readable medium having instructions stored therein that, when executed by one or more processors, cause the one or more processors to perform a method for classifying Partial Discharge (PD) in an electrical equipment, comprising:

• detecting, by an acoustic emission sensor, a mechanical wave produced by an electrical discharge event and converting the mechanical wave into an audio signal;
• determining, by a signal preprocessing unit, a waveform of the audio signal and converting the determined waveform into a waveform image, wherein the converting includes performing a Short-Time Fourier Transform (STFT) on the audio signal to preserve time information and further to convert the audio signal into a spectrogram as the waveform image;
• predicting, by a processing circuitry configured with a Convolution Neural Network (CNN) that takes as input the waveform image, a fault class among four different PD types, which are an arcing, a corona discharge, a tracking, a looseness as well as a healthy equipment;
• and
• outputting, by an output device, an indication of the fault class of the electrical equipment.