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.
Keywords
Cables
Chaos theory
Complex networks
Defects
Diagnosis
Networks (circuits)
Permittivity measurement
Reflection
Reflectometers
Signal to noise ratio
Topology
Wire
Defect detection
Detection performance
Distributed diagnosis
Noise robustness
Noisy environment
Operational usage
Reflectometry
Time domain reflectometry
Time domain analysis