Title :
Extracting noise using time-frequency profile plot
Author :
Yang, Jianguo ; Song, Wanqing
Author_Institution :
Coll. of Mech. Eng., Donghua Univ., Shanghai, China
Abstract :
The objective of this paper is to introduce Newland Harmonic wavelets and Richman -Moorman (2000) sample entropy are applied to detect singularity signal on worn tool. Because some weak vibration signals contained strong noises are very important for fault forecast. Based on harmonic wavelet mesh plot of the vibration signals, we can induce contours of the mesh map with log space, then, we offer the time-frequency profile plot from the mesh map. This time-frequency profile plot is corresponding to decompose level on harmonic wavelets. Final, by computing sample entropy in each level time-frequency profile plot, the weak cycle signal can be easily extracted from strong noise.
Keywords :
cutting tools; entropy; fault diagnosis; harmonic analysis; interference suppression; machine tools; signal detection; time-frequency analysis; turning (machining); vibrations; wavelet transforms; wear; Newland harmonic wavelets; Richman-Moorman sample entropy; fault forecast; mesh profile plot; noise extraction; singularity signal detection; time-frequency profile plot; weak vibration signal; worn tool; Educational institutions; Entropy; Fourier transforms; Machining; Mechanical engineering; Noise level; Signal detection; Surface waves; Time frequency analysis; Vibrations; frequency ma; harmonic wavelet; mesh profile plot; sample entropy; wear tool;
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7737-1
DOI :
10.1109/MACE.2010.5536679