Partial Discharge Feature Extraction and Diagnosis of Industrial Acoustic Imaging Equipment Based on Time-Frequency Analysis

Based on the project framework of “High end Testing Equipment and Systems - Key Technology Research and System Development of Industrial Acoustic Imager”, this study proposes a time-frequency analysis based method for extracting and diagnosing partial discharge characteristics of industrial acoustic imager. The method achieves efficient extraction and accurate diagnosis of partial discharge features by in-depth analysis of the time-frequency characteristics of acoustic signals and combining advanced signal processing techniques. In the detection accuracy experiment, the detection accuracy of normal signals reached 92<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sup>/0, and the recall rate of partial discharge signals was 95%. From the experimental data conclusion, it can be seen that the time-frequency analysis method performs well in terms of detection accuracy and is suitable for partial discharge detection and diagnosis in complex industrial environments.