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

Summary

This protocol presents a maximum-entropy spectral-estimation-based method for precise defect localization in long power distribution cables using frequency-domain reflectometry. It details high-frequency cable modeling, reflection coefficient spectrum analysis, spectral extrapolation, and validation via simulations and experiments, achieving superior accuracy compared to conventional FFT approaches.

Abstract

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.

Introduction

With the increasing demand for power supply reliability and safety in modern power systems, cables have been widely adopted in urban distribution networks. Among them, cross-linked polyethylene (XLPE) cables are extensively utilized due to the author’s outstanding advantages^1,2. Distribution cables are typically installed underground, where the operating environment is harsh. As service time increases, combined with load fluctuations and overloading, cable aging becomes more pronounced. Consequently, localized defects such as water trees, electrical trees, partial discharges, and insulation moisture may ....

Protocol

NOTE: Perform all measurements on the test cable in an offline state (de-energized). Use a vector network analyzer (VNA) or equivalent frequency-domain reflectometry instrument capable of swept-frequency signal injection and reflection coefficient acquisition. Ensure the cable is open-circuited at the far end unless otherwise specified. Minimize connection reflections by using short, direct coaxial connections and conductive tape for secure contact. Refer to the Table of Materials for recommended equipment and software.

1. Prepare the cable sample and measurement setup

1. Select the power distribut....

Results

The reflection coefficient spectrum and defect localization results were obtained from both simulations and experiments using the maximum entropy spectral method and compared with conventional FFT-based approaches. A successful defect localization is characterized by a smooth power spectrum with a sharp, prominent peak at the exact defect position, minimal spurious peaks (pseudopeaks caused by sidelobes or leakage), and a low relative error (typically <0.3%). In contrast, suboptimal results from conventional FFT metho.......

Discussion

In this study, the authors present a detailed protocol for localizing defects in power distribution cables using frequency-domain reflectometry (FDR) enhanced by the maximum entropy spectral (MES) method. Previous studies have often relied on conventional fast Fourier transform (FFT)-based analysis, which struggles with spectral leakage, limited resolution in long cables, and spurious peaks that complicate defect identification³⁴. Additionally, researchers without advanced signal processing expert.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Conductive copper tape, double-sided	Not specified	N/A	Used for connecting test leads to the cable core and shield to minimize head-end reflection interference https://www.shcenxin.com/metaltape/93.html
YJLV22-8.7/10 kV-3×70 medium-voltage cable	Not specified	YJLV22-8.7/10 kV-3×70	Cross-linked polyethylene (XLPE) aluminum core steel tape armored PVC sheathed power cable; total length 171 m; used as test object with externally induced defect http://www.xmdl518.com/jspn01-Products-6234877/
10 kV cable defect localization device	Not specified	Not specified	Frequency-domain reflectometry instrument; frequency band 100 kHz–50 MHz; configured with 5,001 sampling points for reflection coefficient spectrum acquisition https://www.163.com/dy/article/K6OHFJOO0552X57P.html