Power Distribution Cable Defect Localization Technology Based on the Maximum Entropy Spectral Method

As cable laying distances in modern urban distribution networks continue to expand, the accuracy of fault location via frequency-domain reflectometry (FDR) diminishes markedly with increasing length. To improve precision for long cables, this study proposes a maximum-entropy spectral-estimation-based method. A high-frequency distributed parameter model for distribution cables is developed to quantitatively assess the impacts of insulation aging and mechanical damage on per-unit-length capacitance and inductance. Drawing on transmission line theory, the relationship between the reflection coefficient spectrum and the defect position is derived, along with a step-frequency optimization criterion to enhance spectral resolution. To mitigate spectral leakage and limited resolution in fast Fourier transform (FFT)-based frequency-domain analysis, the maximum entropy spectral method is employed for high-fidelity spectrum estimation, thereby elevating fault distance localization accuracy. Simulations reveal that, relative to conventional FFT, the proposed method reduces location errors by 2-4.5 times in typical long-cable cases. Experimental results confirm a relative error below 0.25% for the maximum entropy approach, surpassing the conventional method's error under 0.55%, thus validating its efficacy and superiority in engineering practice.