Abstract
The neural network diagnosis method based on fault features denoted by frequency domain kernel in nonlinear circuit was presented here. Each order frequency domain kernel of circuit response under all fault states can be got by vandermonde method; the circuit features extracted was preprocessed and regarded as input samples of neural network, faults is classified. The uniform recurrent arithmetical formula of each order frequency-domain kernel was given, the Volterra frequency-domain kernel acquisition method was discussed, and the fault diagnosis method based on recurrent neural network was showed. A fault diagnosis illustration verified this method. The fault diagnosis method showed the advantages: no precise circuit model is needed in avoiding the difficulty in identifying nonlinear system online, less computation amount, high fault diagnosis efficiency.
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© 2006 Springer-Verlag Berlin Heidelberg
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Yuan, H., Chen, G. (2006). Fault Diagnosis in Nonlinear Circuit Based on Volterra Series and Recurrent Neural Network. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893295_57
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DOI: https://doi.org/10.1007/11893295_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46484-6
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