A Novel Cable Fault Detection Method Based on Collaborative Characterization of Step Response and Impulse Response

As a critical component of urban power supply systems, power cables require early detection of soft faults such as insulation aging and mechanical damage to ensure the safety of the power grid. This paper proposes a cable fault detection method based on the synergistic characterization of step and impulse responses. First, a mathematical model of the broadband reflection coefficient spectrum of the cable is established based on transmission line theory, and the mapping relationship between the reflection coefficient and cable characteristic impedance variation is derived. Then, the frequency-domain reflection coefficient is transformed into the time domain via inverse Fourier transform, and a synergistic characterization method using step and impulse responses is developed through convolution operations. To validate the effectiveness of the proposed method, a 10 kV single-core XLPE distribution cable model is built on the Matlab platform, and an experimental platform is constructed using a vector network analyzer and a step signal generator. Simulation and experimental results show that the proposed method achieves a fault localization error of less than $0.8 \%$ in simulation and can accurately identify typical faults such as water ingress, outer shielding damage, and cable joint issues during field tests.