A new technique is proposed to reconstruct faulty wiring networks from the time-domain reflectometry (TDR) response. The developed method is also for characterization of defects in the branches of the network. The direct problem (propagation along the cables) is modeled by RLCG circuit parameters computed by finite element method (FEM) and the finite-difference time domain (FDTD) method. Genetic algorithms (GAs) are used to solve the inverse problem. The proposed method allows to accurately locate wire faults. Some examples are presented to validate and illustrate the ability of this reconstruction method.

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.

The design of dielectric materials with artificial molecules formed by electrically small dipole antennas loaded with passive electrical circuit elements is considered. Variations in the antenna loads lead to known and generalizations of known dielectric material models. These artificial dielectrics are characterized in terms of their equivalent susceptibilities and polarization vectors both in the frequency and time domains. With suitable choices in the antenna loads one can design the loss and dispersion properties of the resultant materials.

The electromagnetic properties of artificial molecules composed of small linearly loaded antennas embedded in a host medium are derived and discussed. It is demonstrated that the electromagnetic ch...

From reflectometry methods, this work aims at locating accurately electrical faults in complex wiring networks. Increasing demand for online diagnosis has imposed serious challenges on interference mitigation. In particular, diagnosis has to be carried out while the target system is operating. The interference becomes more even critical in the case of complex networks where distributed sensors inject their signals simultaneously. The objective of this paper is to develop a new embedded diagnosis strategy in complex wired networks that would resolve interference problems and eliminate ambiguities related to fault location. To do so, OMTDR (Orthogonal Multi-tone Time Domain Reflectometry) method is used. For better coverage of the network, communication between sensors is integrated using the transmitted part of the OMTDR signal. It enables data control and transmission for fusion to facilitate fault location. In order to overcome degradation of diagnosis reliability and communication quality, we propose a new sensor clustering strategy based on network topology in terms of distance and number of junctions. Based on CAN bus network, we prove that data fusion using sensor clustering strategy permits to improve the diagnosis performance.