Title :
A new wavelet coefficients correlation denoising method applied in fault detection
Author_Institution :
Coll. of Inf. Eng., Shenyang Univ., Shenyang, China
Abstract :
In fault detection of power system, the detection for mutations signal is very important. The application of wavelet coefficients correlation denoising in signal detection for noisy fault problem is relatively widespread. However, after doing wavelet transform to the noisy signal, the wavelet coefficients of each scale will produce a small offset. This paper presents a wavelet coefficients correlation denoising method based on the cross-correlation function. Cross-correlation algorithm is used to calculate the offset between each scale coefficient and original noisy fault signal. Then do correlation analysis to the shift scale signal to get accurate mutation signal, so as to determine the location of faults.
Keywords :
correlation methods; fault diagnosis; power system faults; signal denoising; signal detection; wavelet transforms; cross correlation algorithm; fault detection; mutations signal; noisy fault signal; signal detection; wavelet coefficients correlation denoising method; wavelet transform; Correlation; Noise; Noise measurement; Noise reduction; Power systems; Wavelet coefficients; Coefficient of Correlation; Cross-correlation Function; Fault Signal; Offset and Denoising;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
DOI :
10.1109/WCICA.2012.6358322