UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

An algorithm to remove noise from locomotive bearing vibration signal based on self-adaptive EEMD filter

Wang, C-S; Sha, C-Y; Su, M; Hu, Y-K; (2017) An algorithm to remove noise from locomotive bearing vibration signal based on self-adaptive EEMD filter. Journal of Central South University , 24 (2) pp. 478-488. 10.1007/s11771-017-3450-8. Green open access

[img]
Preview
Text
Hu_Manuscript.pdf - Accepted version

Download (673kB) | Preview

Abstract

An improved ensemble empirical mode decomposition (EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode mixing problem. The algorithm has been validated with a simulation signal and locomotive bearing vibration signal. The results show that the proposed self-adaptive EEMD algorithm has a better filtering performance compared with the conventional EEMD. The filter results further show that the feature of the signal can be distinguished clearly with the proposed algorithm, which implies that the fault characteristics of the locomotive bearing can be detected successfully.

Type: Article
Title: An algorithm to remove noise from locomotive bearing vibration signal based on self-adaptive EEMD filter
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s11771-017-3450-8
Publisher version: http://doi.org/10.1007/s11771-017-3450-8
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: locomotive bearing; vibration signal enhancement; self-adaptive EEMD; parameter-varying noise signal; feature extraction
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10066818
Downloads since deposit
45Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item