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    Abstract
2013 (Vol. 6, Issue: 05)
Article Information:

Mode Parameters Estimation of Vibration Signal Based on Aberrant Point Clustering and Elimination

Ye Qingwei, Wang Dandan and Zhou Yu
Corresponding Author:  Ye Qingwei 

Key words:  Frequency response outliers, K-means clustering algorithm, levy algorithm, polynomial fitting, , ,
Vol. 6 , (05): 802-806
Submitted Accepted Published
September 03, 2012 October 05, 2012 June 25, 2013
Abstract:

A new mode parameter estimation method of vibration signal is put forward in this study. At first, the frequency response curve of vibration signal is fitted by Levy polynomial and the each distance between the fitted curve point and the frequency response curve point is calculated. Then the distance set is clustered by k-means algorithm into two classes. One class is clustered with smaller distance points and another class is clustered with larger distance points which are named aberrant point set. The class of larger distance points clustered will be eliminated and the new frequency response curve is obtained. At last, the new frequency response curve is fitted by Levy polynomial again and the new aberrant point set is eliminated again and so on. Finally, the fitting accuracy will be arrived according to the above algorithm. Plenty of simulation tests to vibration signals show that this algorithm can accurately extract mode parameters of the vibration frequency spectrum. It also confirms that in the different noise intensity and different distance between adjacent frequency cases, the precision of the algorithm proposed by this study is obviously superior to the existing Levy algorithm.
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  Cite this Reference:
Ye Qingwei, Wang Dandan and Zhou Yu, 2013. Mode Parameters Estimation of Vibration Signal Based on Aberrant Point Clustering and Elimination.  Research Journal of Applied Sciences, Engineering and Technology, 6(05): 802-806.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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