Estimation of Distributed and Lumped Ohmic Losses in Electrical Cables

Nassif Berrabah 1 Maud Franchet 2 Denis Vautrin 2 Qinghua Zhang 1
1 I4S - Statistical Inference for Structural Health Monitoring
IFSTTAR/COSYS - Département Composants et Systèmes, Inria Rennes – Bretagne Atlantique
Abstract : Cables play an important role in many industrial systems, from power transmission to data communication. Wired connections are often operated under severe conditions and may be subject to damages or undergo accelerated aging. In order to ensure safe and cost-efficient operations, as well as a high level of performance, efficient tools are needed to assess and monitor the condition of cables. Hard-fault (open or short circuits) are well handled by existing techniques. On the contrary, soft-fault diagnosis still represents an important challenge for current researches. Indeed, their presence in sensor signals is hardly noticeable, while they may be early warning signs of serious failures. This paper focuses on the detection, localization, and estimation of resistive soft fault in electrical cables from reflectometry measurements. A method that enables the computation of the distributed resistance profile R(z) along the cable under test is presented. Both experimental and simulation results are shown as proof of efficiency.
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Communication dans un congrès
2016 IEEE International Conference on Antenna Measurements & Applications, Oct 2016, Syracuse, United States. 2016, 2016 IEEE International Conference on Antenna Measurements & Applications
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Soumis le : mercredi 5 octobre 2016 - 16:53:50
Dernière modification le : mercredi 11 avril 2018 - 02:01:12
Document(s) archivé(s) le : vendredi 6 janvier 2017 - 14:15:28

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Nassif Berrabah, Maud Franchet, Denis Vautrin, Qinghua Zhang. Estimation of Distributed and Lumped Ohmic Losses in Electrical Cables. 2016 IEEE International Conference on Antenna Measurements & Applications, Oct 2016, Syracuse, United States. 2016, 2016 IEEE International Conference on Antenna Measurements & Applications. 〈hal-01376833〉

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