Arcing fault detection using wavelet transform

Abstract An alternative methodology for fault detection of industrial processes based on wavelet transform is proposed. Due to its ability to detect singularities in signals and to perform denoising by means of thresholds, the proposed method is suitable to detection purpose when no model can be achieved for the process. Moreover, fault occurrence time location may be set up. In this paper, a detection method based on multiresolution analysis and coefficients thresholding is explained. An original thresholds computation based upon a multi objective optimization method is developed. Some information for online implementation on DSP is given. Then, the method is applied to industrial arcing fault data.

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