The combination of empirical mode decomposition and minimum entropy deconvolution for roller bearing diagnostics in non-stationary operation

Ricci, R., Borghesani, P., Chatterton, S., & Pennacchi, P. (2012) The combination of empirical mode decomposition and minimum entropy deconvolution for roller bearing diagnostics in non-stationary operation. In Proceedings of the ASME Design Engineering Technical Conference, ASME, Chicago, Illinois, USA, pp. 723-730.

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Abstract

Diagnostics is based on the characterization of mechanical system condition and allows early detection of a possible fault.

Signal processing is an approach widely used in diagnostics, since it allows directly characterizing the state of the system. Several types of advanced signal processing techniques have been proposed in the last decades and added to more conventional ones. Seldom, these techniques are able to consider non-stationary operations. Diagnostics of roller bearings is not an exception of this framework.

In this paper, a new vibration signal processing tool, able to perform roller bearing diagnostics in whatever working condition and noise level, is developed on the basis of two data-adaptive techniques as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED), coupled by means of the mathematics related to the Hilbert transform.

The effectiveness of the new signal processing tool is proven by means of experimental data measured in a test-rig that employs high power industrial size components.

Impact and interest:

5 citations in Scopus
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ID Code: 66496
Item Type: Conference Paper
Refereed: No
Additional Information: ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference.
Volume 1: 24th Conference on Mechanical Vibration and Noise, Parts A and B
Additional URLs:
Keywords: Advanced signal processing; Bearing diagnostics, Minimum Entropy Deconvolution, Bearing diagnostics, Empirical Mode Decomposition
DOI: 10.1115/DETC2012-71012
ISBN: 9780791845004
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300) > Dynamics Vibration and Vibration Control (091304)
Divisions: Current > Schools > School of Chemistry, Physics & Mechanical Engineering
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 by ASME
Deposited On: 22 Jan 2014 00:30
Last Modified: 01 Apr 2014 23:07

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