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A Model-Based Probabilistic Inversion Framework for Characterizing Wire Fault Detection Using TDR
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DOI：10.1109/TIM.2011.2105030.png)
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Time-domain reflectometry (TDR) is one of the standard methods for diagnosing faults in electrical wiring and interconnect systems, with a long-standing history focused mainly on hardware development of both high-fidelity systems for laboratory use and portable handheld devices for field deployment. While these devices can easily assess distance to hard faults such as sustained opens or shorts, their ability to assess subtle but important degradation such as chafing remains an open question. This paper presents a unified framework for TDR-based chafing fault detection in lossy coaxial cables by combining an S-parameter-based forward-modeling approach with a probabilistic (Bayesian) inference algorithm. Results are presented for the estimation of nominal and faulty cable parameters from laboratory data.
Keyword:
Bayesian
fault detection
S-parameters
time-domain reflectometry (TDR)
wiring
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Analysis of spread spectrum time domain reflectometry for wire fault location用于导线故障定位的扩频时域反射法分析.png)
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