Application of PSO-optimized Chebyshev Window Function in Power Cable Defect Detection

Due to the compact closed structure of power cables, it is difficult to perform positioning detection when a defect occurs. Frequency Domain Reflectometry (FDR) is a mature cable testing technology that utilizes swept frequency signals to enhance the accuracy of defect localization. This paper employs Discrete Fourier Transform (DFT) to obtain the localization spectrum and uses Particle Swarm Optimization (PSO) to select optimal parameters for the Chebyshev window function. It can optimiz the waveform of the localization spectrum and improve defect localization accuracy. The results indicate that arbitrary settings of the window function can potentially diminish the defect waveform, leading to misjudgments. In contrast, incorporating the PSO algorithm significantly enhances the peak value of the defect waveform, effectively reduces misjudgments, and improves the reliability of defect localization, demonstrating promising application prospects. Keywords-defect localization, frequency domain reflectometry (FDR), particle swarm optimization (PSO), chebyshev window