In time domain reflectometry (TDR) attenuation and dispersion of the reflected signal limit the reachable accuracy for wire faults location. Because time of flight is evaluated, the wire faults with small impedance changing are difficult to locate. In this paper, a novel method for the TDR-based wire fault detection is presented by transfer function analysis in the time domain. For the determination of the transfer function, a deconvolution should be carried out. Thereby, an inverse problem is to be solved by an adaptive filter approach. Adaptive filters are able to reduce spurious noise of the deconvolution and lead to an acceptable deconvolution estimate. Therefore, a high signal-to-noise-ratio can be reached. The filter's stopband characteristics are optimized by optimization technique to reduce the noise components of the transfer function in the frequency domain. For that a nonlinear fitting procedure is proposed using the Riad-Parruck optimization criterion. The developed method can locate both hard faults (open and short circuits) and soft faults with small impedance changes, and identify the type of wire faults simultaneously in a controlled laboratory environment (without the impedance changes from mechanical vibration, movement, and moisture). The algorithm using adaptive filters and optimization techniques is proposed in this paper for the traditional TDR method, but it is general for most other reflectometry approaches. The estimated wirings are coaxial cables and twisted pair cables, which are used in electrical and power distribution systems.
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