Wavelet Packets Analysis and Artificial Intelligence Based Adaptive Fault Diagnosis
نویسندگان
چکیده
Former fault diagnosis algorithms for the transmission systems usually employ FFT and deterministic thresholds. These bring simplicity along with lots of manual works and inaccuracy to the applications. This paper proposes a new adaptive fault diagnosis scheme, which hardly need any interference from users. It utilizes the Wavelet Packets Transformation Analysis (WPTA) as a preliminary feature extractor and a Neural Network (NN) as the pattern classifier. Extensive simulation studies show that the wavelet packets transform provides an effective signal representation for classification. The combination of the WPTA and NN achieves outstanding performance and the ability to adapt to various network settings. Without any structure modification, the scheme can be applied to different networks. Keyword: system protection, wavelet packets, neural networks,
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