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Estimation of a Cable Resistance Profile with Readaptation of Mismatched Measurement Instrument

Nassif Berrabah 1, 2 Qinghua Zhang 1 Maud Franchet 2 Denis Vautrin 2
1 I4S - Statistical Inference for Structural Health Monitoring
IFSTTAR/COSYS - Département Composants et Systèmes, Inria Rennes – Bretagne Atlantique
Abstract : As the cumulative length of electric cables in modern systems is growing and as these systems age, it becomes of crucial importance to develop efficient tools to monitor the condition of wired connections. Therein, in contrast to hard faults (open or short circuits), the diagnosis of soft-faults requires a particular effort. Indeed, these faults are more difficult to detect, yet they are sometimes early warning signs of more important failures. In a previous paper, we proposed a method to compute the resistance profile R(z) of a cable from reflectometry measurements made at both ends of the cable. It enables detection, localization and estimation of dissipative soft-faults. In this paper, we propose an improvement of this method in case of impedance mismatch between the measurement instrument and the cable, based on a pre-processing of the measurement data before running the estimation computations. It aims at reducing the impedance mismatch between instrumentation and the cable under test without physical intervention on the test fixtures. In addition , this paper proposes a measurement procedure allowing us to get the two-ends reflectometry measurements without actually connecting both ends of the cable under test to a single instrument.
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https://hal.inria.fr/hal-01592434
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Submitted on : Sunday, September 24, 2017 - 1:07:50 PM
Last modification on : Tuesday, December 8, 2020 - 10:20:25 AM
Long-term archiving on: : Tuesday, December 26, 2017 - 11:27:39 AM

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Nassif Berrabah, Qinghua Zhang, Maud Franchet, Denis Vautrin. Estimation of a Cable Resistance Profile with Readaptation of Mismatched Measurement Instrument. International Conference on Electromagnetics in Advanced Applications (ICEAA 2017) , Sep 2017, Verona, Italy. ⟨hal-01592434⟩

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