基于反射频谱Z变换的电缆瞬时性电穿通道诊断

doi:10.19595/j.cnki.1000-6753.tces.241599

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Abstract Transient arc breakdown is recognized as an important precursor to permanent faults in power cables. Currently, diagnostic methods for such faults primarily depend on the online monitoring of arc signals. Due to the randomness and rapid changes associated with transient arcs, along with interference from noise signals, the challenges in locating and identifying these faults of this method are significant. Given that transient arcs may create carbonized breakdown channels in cable insulation, causing reflections of traveling waves, the feasibility of employing offline wave reflection methods for diagnostics has been explored. The frequency domain reflection (FDR) method, noted for its high sensitivity to slight impedance changes, is utilized in this study to diagnose channel defects induced by transient arc breakdown and to establish identification criteria. However, traditional FDR diagnostic curves are plagued with many interfering waveforms, making it challenging to determine the type of defect. To address these issues, an improved Z-transform algorithm is proposed in this paper, and transient arc breakdown channel defects are prepared, ensuring high location accuracy and sensitivity while facilitating the discrimination of defect types.
First, an equivalent electrical circuit model of the power cable under distributed parameters is constructed, from which the reflection coefficient spectrum (RCS) at the cable's head end is derived. The application of the Z-transform algorithm to process the RCS and the settings of various parameters are then thoroughly analyzed. Despite these measures, the diagnostic results still contain numerous sidebands and interfering waveforms, and the polarity information of the reflection coefficients cannot be discerned. Considering the wide applications of the hyperbolic secant pulse, a rapidly attenuating and smoothly transitioning unipolar wave in fields such as signal processing, communications, and fiber optics, this pulse is employed to modulate the RCS and to refine the Z-transform. Moreover, various types of defects are set up on a 500-meter-long simulated cable for diagnostic validation. The improved algorithm is shown to maintain high location accuracy and sensitivity, providing correct criteria for defect types based on the polarity information of the reflection coefficients.
Subsequently, an experimental platform for transient arc breakdown is designed and assembled using experimental transformers, voltage divider, voltage probes and current probes among other devices. The defects produced experimentally are confirmed as transient arc breakdown channels through the analysis of online waveforms and defect cross-sections. And then the improved algorithm and traditional FDR method are applied to process the reflection coefficient spectrum at the first end of the defective cable, and time-domain reflectometry (TDR) is used for comparison in diagnosing the defective cable. The diagnostic results from the improved Z-transform algorithm indicate that the position error of the breakdown channel is less than 0.5%, identifying it as an inductive defect. In contrast, TDR results are unable to ascertain the defect's location, and although the traditional FDR method achieves defect localization, it does so with a location error of approximately 6%, accompanied by numerous interfering waveforms, failing to provide criteria for defect type.
In conclusion, the improved Z-transform algorithm proposed in this paper ensures a location accuracy of less than 0.5% for transient arc breakdown channels and provides criteria for their classification, deducing them to be inductive defects. This offers a potent algorithm and valid criteria for diagnosing such incipient faults in the maintenance of cable transmission and distribution lines.

Key words： Power cable transient electric arc breakdown defect diagnosis reflection coefficient Z-transform

Received: 10 September 2024

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TM247

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	He Guanghua
	Jin Yan
	Feng Yao
	Qi Jinlong
	Zhao Jiahao

Cite this article:

He Guanghua,Jin Yan,Feng Yao等. Diagnosis of Cable Transient Electric Arc Breakdown Channel Based on Z-Transform of Reflection Coefficient Spectrum[J]. Transactions of China Electrotechnical Society, 2025, 40(17): 5615-5625.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.241599 OR https://dgjsxb.ces-transaction.com/EN/Y2025/V40/I17/5615

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