Abstract
Time Domain Reflectometry (TDR) is commonly used to detect and localize hard faults in electric network. Unfortunately, in the case of soft fault especially in the case of complex network (network with several branches) it remains very difficult to detect the affected branch. In order to resolve this problem, we propose a new approach based on the Time Domain Reflectometry combined with Neural Network method (NN); the response of the electric network is obtained by applying the Finite Difference Time Domain method (FDTD) on the transmission line equations and the inverse problem is solved using Neural Network, very acceptable results are obtained basing on our new strategy which is capable to: define the fault by given the correct value of both of resistance and position, define the state of electrical network online, detect and localize more than one soft fault.
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Laib, A., Melit, M., Nekhoul, B., El Khamlichi Drissi, K., Kerroum, K. (2019). Soft Fault Identification in Electrical Network Using Time Domain Reflectometry and Neural Network. In: Chadli, M., Bououden, S., Ziani, S., Zelinka, I. (eds) Advanced Control Engineering Methods in Electrical Engineering Systems. ICEECA 2017. Lecture Notes in Electrical Engineering, vol 522. Springer, Cham. https://doi.org/10.1007/978-3-319-97816-1_28
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DOI: https://doi.org/10.1007/978-3-319-97816-1_28
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