Transformer Partial Discharge Experimental Data Processing with MATLAB Implementation

Transformer partial discharge testing serves as a critical component in transformer maintenance diagnostics. This MATLAB-based program provides comprehensive data processing capabilities for analyzing discharge waveforms through multiple algorithmic approaches. The implementation includes digital signal processing techniques for noise reduction using wavelet transform or adaptive filtering methods, enabling cleaner signal analysis. The program automatically detects waveform peaks through threshold-based algorithms or derivative analysis, calculating amplitude characteristics and discharge magnitudes. Phase information extraction utilizes zero-crossing detection or Hilbert transform methods to determine discharge timing relative to the power frequency cycle. The code structure incorporates modular functions for data input validation, signal preprocessing, feature extraction, and result visualization. Through this program, engineers can perform quantitative analysis of partial discharge patterns, identify insulation defects, and predict potential transformer failures by analyzing discharge intensity, phase distribution, and repetition rates. The implementation supports both time-domain and phase-resolved partial discharge analysis for comprehensive transformer condition assessment.