Applications of wavelets and sparse decomposition in non-continuous film de-noising
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1.
School of Electronic Information and Electrical Engineering, Changzhou Institute of Technology, Changzhou 213022, China
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Received Date:
2013-08-20
Accepted Date:
2013-09-02
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Abstract
In order to avoid measuring the inherent frequency and the scanning vibration frequency of C-dynamic scanning system before measuring discontinuous film thickness of lithium battery with laser sensors, the 3-layer wavelet-threshold judgment-sparse decomposition signal processing de-noising method was used. Theoretical analysis and experimental verification were made. Without prior knowledge of the inherent frequency and the scanning vibration frequency and under different C-dynamic scanning mode, the best-matching atomic sequence was selected by iteration and the film thickness distribution of lithium battery was reserved, fluctuations of the local noise were filtered and sparse iterative de-noising was realized. The results show that comparing with the wavelet algorithm and in the absence of the prior knowledge, sparse decomposition algorithm has better de-noising performance and is a simple, practical and effective method. Mean square error of sparse decomposition algorithm is 5μm~7μm.
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