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Chaos Time Domain Reflectometry for Online Defect Detection in Noisy Wired Networks

Abstract : In many application domains, wire faults can have dramatic consequences. Live wire diagnosis is often required to ensure permanent monitoring of the health of embedded cables. A novel reflectometry-based method for online wire diagnosis is presented. Chaos time domain reflectometry (CTDR) takes benefit of the properties of chaotic signals and shows very good potential for the diagnosis of live wires (i.e., during their operational usage) and complex topology networks. In particular, CTDR shows high performances in very noisy environments: the detection and the location of hard defects are possible even in the case of negative signal to noise ratio and if several reflectometers inject their signals in the cable. This enables using CTDR for the distributed diagnosis of live complex topology networks of lengths up to several tens of meters. CTDR's defect detection capacity is shown and experimentally verified: increasing the length of the probe signal lowers the noise level. A noise robustness analysis provides a means to choose the signals parameters necessary to ensure specified detection performances.
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https://hal-cea.archives-ouvertes.fr/cea-01846862
Contributor : Léna Le Roy <>
Submitted on : Monday, July 23, 2018 - 8:01:14 AM
Last modification on : Monday, February 10, 2020 - 6:14:16 PM

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F. Auzanneau, N. Ravot, L. Incarbone. Chaos Time Domain Reflectometry for Online Defect Detection in Noisy Wired Networks. IEEE Sensors Journal, 2016, 16 (22), pp.8027-8034. ⟨10.1109/JSEN.2016.2606567⟩. ⟨cea-01846862⟩

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