PMID- 29880275
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20181004
LR  - 20181004
IS  - 1879-2022 (Electronic)
IS  - 0019-0578 (Linking)
VI  - 80
DP  - 2018 Sep
TI  - Incipient fault feature extraction of rolling bearings based on the MVMD and 
      Teager energy operator.
PG  - 297-311
LID - S0019-0578(18)30214-3 [pii]
LID - 10.1016/j.isatra.2018.05.017 [doi]
AB  - Aiming at the problems that the incipient fault of rolling bearings is difficult 
      to recognize and the number of intrinsic mode functions (IMFs) decomposed by 
      variational mode decomposition (VMD) must be set in advance and can not be 
      adaptively selected, taking full advantages of the adaptive segmentation of scale 
      spectrum and Teager energy operator (TEO) demodulation, a new method for early 
      fault feature extraction of rolling bearings based on the modified VMD and Teager 
      energy operator (MVMD-TEO) is proposed. Firstly, the vibration signal of rolling 
      bearings is analyzed by adaptive scale space spectrum segmentation to obtain the 
      spectrum segmentation support boundary, and then the number K of IMFs decomposed 
      by VMD is adaptively determined. Secondly, the original vibration signal is 
      adaptively decomposed into K IMFs, and the effective IMF components are extracted 
      based on the correlation coefficient criterion. Finally, the Teager energy 
      spectrum of the reconstructed signal of the effective IMF components is 
      calculated by the TEO, and then the early fault features of rolling bearings are 
      extracted to realize the fault identification and location. Comparative 
      experiments of the proposed method and the existing fault feature extraction 
      method based on Local Mean Decomposition and Teager energy operator (LMD-TEO) 
      have been implemented using experimental data-sets and a measured data-set. The 
      results of comparative experiments in three application cases show that the 
      presented method can achieve a fairly or slightly better performance than LMD-TEO 
      method, and the validity and feasibility of the proposed method are proved.
CI  - Copyright (c) 2018. Published by Elsevier Ltd.
FAU - Ma, Jun
AU  - Ma J
AD  - Faculty of Mechanical and Electrical Engineering, Kunming University Science and 
      Technology, Kunming 650500, China.
FAU - Wu, Jiande
AU  - Wu J
AD  - Fauclty of Information Engineering and Automation, Kunming University of Science 
      and Technology, Kunming 650500, China; Engineering Research Center for Mineral 
      Pipeline Transportation YN, Kunming 650500, China. Electronic address: 
      491941203@qq.com.
FAU - Wang, Xiaodong
AU  - Wang X
AD  - Fauclty of Information Engineering and Automation, Kunming University of Science 
      and Technology, Kunming 650500, China; Engineering Research Center for Mineral 
      Pipeline Transportation YN, Kunming 650500, China.
LA  - eng
PT  - Journal Article
DEP - 20180605
PL  - United States
TA  - ISA Trans
JT  - ISA transactions
JID - 0374750
OTO - NOTNLM
OT  - Incipient fault feature extraction
OT  - Modified variational mode decomposition
OT  - Spectral segmentation
OT  - Teager energy operator
EDAT- 2018/06/09 06:00
MHDA- 2018/06/09 06:01
CRDT- 2018/06/09 06:00
PHST- 2017/07/07 00:00 [received]
PHST- 2018/05/17 00:00 [revised]
PHST- 2018/05/22 00:00 [accepted]
PHST- 2018/06/09 06:00 [pubmed]
PHST- 2018/06/09 06:01 [medline]
PHST- 2018/06/09 06:00 [entrez]
AID - S0019-0578(18)30214-3 [pii]
AID - 10.1016/j.isatra.2018.05.017 [doi]
PST - ppublish
SO  - ISA Trans. 2018 Sep;80:297-311. doi: 10.1016/j.isatra.2018.05.017. Epub 2018 Jun 
      5.