Title :
Feature extraction & application of engineering non-stationary signals based on EMD-approximate entropy
Author :
Lv Jianxin ; Husheng, Wu ; Jie, Tian
Author_Institution :
Dept. of Equip., Eng. Coll. of CAPF, Xi´´an, China
Abstract :
A feature extraction method based on empirical mode decomposition, approximate entropy is proposed. Firstly, the vibration signals are decomposed into a finite number of intrinsic mode functions by empirical mode decomposition. Then, by the means of approximate entropy, the complexity of the original and its intrinsic oscillation modes can be quantified, thereby the intrinsic mode complexity of reciprocating mechanical vibration signals can be quantitatively evaluated. So, the approximate entropies of intrinsic mode functions can serve as the fault characteristic vectors of support vector machine. Finally, the mechanical working condition and faults are classified. The results of engineering application validate the effectiveness of the method.
Keywords :
acoustic signal processing; approximation theory; diesel engines; entropy; fault diagnosis; feature extraction; mechanical engineering computing; support vector machines; vibrations; approximate entropy; empirical mode decomposition; feature extraction method; intrinsic oscillation mode; mechanical vibration signal; nonstationary signal; support vector machine; Approximate entropy; Empirical mode decomposition; Feature extraction; Signal processing; Support vector machine;
Conference_Titel :
Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-7957-3
DOI :
10.1109/CMCE.2010.5610014