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

Auzanneau, Fabrice; Ravot, Nicolas; Incarbone, Luca

doi:10.1109/jsen.2016.2606567

Cited by 27 publications

(10 citation statements)

References 19 publications

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“…Noise-domain reflectometry (NDR) [ 38 ] uses the native noise present in the system. Chaos-domain reflectometry (CDR) injects true noise signals [ 39 ]. Orthogonal multi-tone time-domain reflectometry (OMTDR) enables simultaneous testing and data communication [ 40 , 41 , 42 ].…”

Section: Reflectometrymentioning

confidence: 99%

A SSTDR Methodology, Implementations, and Challenges

Kingston

Benoit

Edun

et al. 2021

Sensors

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Sequence time-domain reflectometry (STDR) and spread spectrum time-domain reflectometry (SSTDR) detect, locate, and diagnose faults in live (energized) electrical systems. In this paper, we survey the present SSTDR literature for discussions on theory, algorithms used in its analysis, and its more prominent implementations and applications. Our review includes both scientific litera-ture and selected patents. We also discuss future applications of SSTDR.

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Section: Reflectometrymentioning

confidence: 99%

A SSTDR Methodology, Implementations, and Challenges

Kingston

Benoit

Edun

et al. 2021

Sensors

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“…As a further matter, an average measurement from 1000 measures must be performed in order to reduce the noise of the test bench. Thus, another method has been proposed in [9], [10]. In [10], it has been demonstrated that a combination between the logistic map and the Bernoulli map leads to a chaotic behavior "choosing properly" the parameters.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, simulations highlight the ability of the hard fault detection for complex wire network. Thus, this chaotic signal is used in [9] to demonstrate the efficiency of the method in a high noisy cable network, and, for real time measurements. From a measurement bench where the chaotic signal is generated with an arbitrary wave generator, the sensitivity analysis carried out in this article was promising for the soft fault detection.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Chaos Time Domain Reflectometry for the Soft Fault Detection in a Cable

Bzikha

Monferran

Velayudhan

et al. 2020

2020 International Symposium on Electromagnetic Compatibility - EMC EUROPE

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This paper proposes to analyze the performance in terms of soft fault detection of two chaotic signals using the chaos time domain reflectometry. These signals which are 1) a combination of the logistic map and Bernoulli map and 2) the Lorenz signal are depicted in order to remind their usage limitations. Although this paper demonstrates the relevance of the proposed chaotic signals for the soft fault detection, we propose also to compare the performances of each signal with a statistical approach. The study leads to conclude than the combination of the logistic map and Bernoulli map is more reliable than the Lorenz signal.Index Terms-chaos time domain reflectometry (CTDR), soft fault detection, chaotic signals comparison

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“…But online network testing without impacting the functionality of a system necessitates specific testing signals that do not interfere with the useful signals operating in the network. Eventually, Spread Spectrum TDR (SSTDR) [10], Multi Carrier TDR (MCTDR) [18], [19], Orthogonal Multi-tone TDR (OMTDR) [20], [21], Chaos TDR (CTDR) [22], [23] and modulated variants of the OMTDR [24], [25] provided promising and robust results in live cablediagnosis. Particularly, they have allowed a complete control of the spectrum of the injected signal which shall not interfere with the system under test (SUT).…”

mentioning

confidence: 99%

Enhancing the Spatial Resolution for Wire Fault Detection Systems Using Multi-Carrier Signals

et al. 2018

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Recently, the world is witnessing a vast daily development in technology accompanied with more and more complex electronic systems. They are hosting cumulated lengths of electrical cables that are subject one day or another to the occurrence of wiring faults. Accordingly, wire diagnosis became essentially important for ensuring safety, security, integrity and optimal performance. On the other hand, the emergence of sensor networks and connected objects have created the need for embedded and non invasive fault diagnosis solutions. Notably, multi-carrier reflectometry methods have shown promising and efficient results in locating upcoming defects on wires in an online manner. Nevertheless, their precision stays within the physical limits of their components, especially the sampling frequency of their analog/digital transitions. In this paper, we will propose several approaches combining multi-carrier reflectometry with phase analysis techniques to overcome this limit. Accordingly, an improvement in the precision of the fault localization and a high spatial resolution is obtained. Based on an FPGA implementation, our novel methods and the resulting systems have proven a fivetimes better accuracy than state-of-the-art methods on the same platform.

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

Cited by 27 publications

References 19 publications

A SSTDR Methodology, Implementations, and Challenges

A SSTDR Methodology, Implementations, and Challenges

Analysis of Chaos Time Domain Reflectometry for the Soft Fault Detection in a Cable

Enhancing the Spatial Resolution for Wire Fault Detection Systems Using Multi-Carrier Signals

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