Title :
Notice of Retraction
Application of EEMD in fault diagnosis of diesel engine
Author :
Shiding Luo ; Lingling Zhang ; Yiguan Zhao ; Yunkui Xiao ; ShengLin Fang
Author_Institution :
Automobile Eng. Dept., Acad. of Mil. Transp., Tianjin, China
Abstract :
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
The principle and algorithm of Empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) is introduced, and two methods are respectively used to analyze simulated signal and engine´s vibration signals. Based on EEMD, the signal can be efficiently decomposed into a finite number of intrinsic mode functions (IMFs) by adding white noise, and the problem of mode mixing in frequency which is drawback of EMD is avoided. Experimental results show that EEMD has obvious superiority to EMD on processing vibration signal, and the method may be applied to fault diagnosis of diesel engine by efficiently extracting fault feature in the marginal Hilbert spectrum.
Keywords :
acoustic signal processing; diesel engines; fault diagnosis; feature extraction; vibrations; white noise; diesel engine; ensemble empirical mode decomposition; fault diagnosis; fault feature extraction; intrinsic mode function; marginal Hilbert spectrum; vibration signal processing; white noise; Algorithm design and analysis; Engines; empirical mode decomposition; ensemble empirical mode decomposition; fault diagnosis; marginal hilbert spectrum;
Conference_Titel :
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5537-9
DOI :
10.1109/ICCSIT.2010.5565053
