Title :
Application of adaptive structure element for generalized morphological filtering in vibratio signal de-noising
Author :
Zhang, Wenbin ; Wang, Hongjun ; Teng, Ruijing ; Xu, Shaokun
Author_Institution :
Eng. Coll., Honghe Univ., Mengzi, China
Abstract :
Aiming at the fault feature was always hidden by strong noise background in vibration signal, a novel de-noising method was proposed based on the adaptive structure element for generalized morphological filtering (ASEGMF). At first, the sine structure element was selected, and the length scale and the height scale were defined according to the feature of vibration signal. Then, the peak interval and the peak height were defined by signal´s local characteristic, and the length scale and the height scale of sine structure element were gotten by adaptive method. In the end, the interrupted vibration signal was de-noised by the generalized morphological filter cascaded by one small and one big adaptive structure elements. This method conquers the selective random of current morphological filter, the structure element are gotten adaptively by signal´s local characteristic without artificial interference. Practical and simulation results show that this approach has better de-nosing effectiveness.
Keywords :
condition monitoring; fault diagnosis; filtering theory; mechanical engineering computing; signal denoising; turbomachinery; vibrations; ASEGMF; adaptive structure element method; artificial interference; condition monitoring; fault diagnosis; fault feature; generalized morphological filtering; rotating machinery; signal local characteristic; sine structure element; vibration signal denoising; Low pass filters; Noise; Noise reduction; Periodic structures; Transforms; Vibrations; adaptive structure element; de-noising; generalized morphological filtering; vibration signal;
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
DOI :
10.1109/CISP.2010.5647582