Analysis of electrochemical noise based on wavelet signal de-nosing

The principle on the electrochemical noise detected by using wavelet transform was described briefly. In the electrochemical noise measurements, there is always having noise more or less. If they are analyzed directly, the useful information and data can not be got from them, so they must be de-nois...

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Bibliographic Details
Main Authors: Hong Men, Caihong Wang, Yan Peng, Shanrang Yang, Zhiming Xu
Format: Conference Proceeding
Language:English
Subjects:
Biomedical signal processing
Butterworth filter
de-noising
electrochemical noise
Information analysis
Noise measurement
Signal analysis
Signal processing
Spline
the quadratic biorthogonal spline wavelet
Time domain analysis
Wavelet analysis
Wavelet domain
wavelet transform
Wavelet transforms
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Summary:The principle on the electrochemical noise detected by using wavelet transform was described briefly. In the electrochemical noise measurements, there is always having noise more or less. If they are analyzed directly, the useful information and data can not be got from them, so they must be de-noised. Wavelet analysis has many advantages that other signal processing tools do not have, it can provide characteristics of the signal both in time domain and frequency domain, it has high resolution, and high resulting accuracy. The electrochemical noise of 304 stainless steel corrosion which is measured in the solution of sulfate-reducing bacteria were de- noised by using a wavelet threshold de-noising method, which made the quadratic biorthogonal spline wavelet as the mother wavelet and adopted an soft threshold processing function. The results showed that the quadratic biorthogonal spline wavelet much smoother and it can remove the noise from the electrochemical noise effectively, and can effectively identify the location of the sudden changes in the signal and accurately reflect the useful information of the signal.
DOI:10.1109/ICICISYS.2009.5358173