Local defect detection of cable impedance spectrum by using fast inverse Fourier transform

Abstract Cables are a key component of power systems. Local defects such as insulation aging and mechanical damage can easily cause serious faults. Impedance spectroscopy analysis has become a research hotspot in defect detection due to its non-invasive nature and sensitivity. However, traditional Fourier transforms have problems such as weak noise suppression, low characteristic resolution, spectral leakage, and insufficient low-frequency resolution, which limit the ability to detect minor defects.To address this limitation and achieve high-precision detection and location of local defects in cables, this paper adopts an improved method based on the fast Inverse fourier transform (IFFT). The equivalent time component 2lv is extracted from the reflection coefficient spectrum at the beginning of the cable, and the time-frequency resolution is optimized by combining the adaptive window function. The defect characteristic frequency band is enhanced through the frequency-domain weighting algorithm, and the location function DFxis constructed to highlight the defect differences. Meanwhile, the signal propagation speed is simulated and measured by COMSOL software to provide key positioning parameters.Experiments show that this method is not sensitive to the strength of the injected signal (as long as the minimum power is met), but sensitive to the severity of defects. It can accurately locate multi-position defects (such as defects at 10m, 20m, and 40m on a 60m XLPE cable), and is not affected by cable curls. It is suitable for high-voltage cables and RF cables with semiconductive layers.