Wire Diagnosis using Reflectometry Response and Optimization Method

Aging wiring in cars, aircraft, trains, and other transportation mean is identified as a critical security area. In this chapter, a new methodology for wire diagnosis allowing the detection, localization and characterization of the fault in wiring network was proposed. Two complimentary steps were addressed. In the first step the direct problem (propagation along the cables) is modelled by RLCG circuit parameters computed by finite elements (FEM) and the Finite Difference Time Domain (FDTD) method. This model provides a simple and accurate method to simulate Time Domain Reflectometry (TDR) responses for simple and Multiconductor Transmission Lines (MTL). In the second step the optimization method is combined with the wire propagation model to solve the inverse problem and to deduce physical information’s about defects from the reflectometry response. For the inverse problem, several approach are study, the iterative and direct inversion using respectively Genetic Algorithm (GA), Partial Swarm Optimization (PSO) or Electromagnetism-Like Mechanism and Neural Network (NN). The method provides an efficient tool for the diagnosis of embedded wire networks. In order to demonstrate the performance and applicability of the proposed method several configurations are studies. A set of experimental results is carried out in order to validate the method.