Abstract
The paper presents a hybrid scheme using a Discrete Wavelet Transform and a Fuzzy Expert System for feature extraction and classification. The signal under test (electrical current or voltage for Power Quality study) is processed through a DWT decomposition block to generate the feature extraction curve. The DWT Level and Energy information from the feature extraction curve is then passed through a diagnostic module that computes the truth-value of the signal combination and determines the class to which the signal belongs. The proposed scheme is much simpler and powerful than currently available PQ classification schemes.
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Tiwari, A.K., Shukla, K.K. (2002). Wavelet Transform Based Fuzzy Inference System for Power Quality Classification. In: Pal, N.R., Sugeno, M. (eds) Advances in Soft Computing — AFSS 2002. AFSS 2002. Lecture Notes in Computer Science(), vol 2275. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45631-7_21
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DOI: https://doi.org/10.1007/3-540-45631-7_21
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