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Condition monitoring of rotating machinery with acoustic emission: a British-Australian collaboration

Crivelli, Davide, Hutt, Simon, Clarke, Alastair, Borghesani, Pietro, Peng, Zhongxiao and Randall, Robert 2019. Condition monitoring of rotating machinery with acoustic emission: a British-Australian collaboration. In: Mathew, Joseph, Lim, C.W., Ma, Lin, Sands, Don, Cholette, Michael E. and Borghesani, Pietro eds. Asset Intelligence through Integration and Interoperability and Contemporary Vibration Engineering Technologies, Lecture Notes in Mechanical Engineering, Cham: Springer, pp. 119-128. (10.1007/978-3-319-95711-1_12)

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Abstract

Industries such as transport and energy generation are aiming to create cleaner, lighter, more reliable and safer technology. Condition monitoring of rotating machinery is an established way of reducing maintenance costs and associated downtime. Whereas vibration based condition monitoring has been validated in literature and in industrial applications, acoustic emission (AE) technologies are a relatively new and unexplored solution for machine diagnostics. Being based on the passive recording of ultrasonic stress waves, their frequency range gives direct access to phenomena such as friction in gear teeth sliding, bearing rolling contacts and crack formation and propagation. However, the complexity of AE signals generated in multiple machine components requires a better understanding of their link with tribological phenomena. To further knowledge in this area, a team of researchers from Cardiff University, Queensland University of Technology and University of New South Wales are conducting a joint research activity which includes: (i) the use of a twin-disk test-rig to reproduce controlled rolling-sliding contact conditions typical of gear contacts, (ii) the analysis of AE data using advanced cyclostationary signal processing and (iii) the establishment of a relationship between tribological conditions and AE signal characteristics. This paper outlines this project, discusses its preliminary results and introduces future extensions of this research to key industrial applications.

Item Type: Book Section
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Springer
ISBN: 978-3-319-95711-1
ISSN: 2195-4356
Funders: EPSRC
Last Modified: 31 Aug 2019 22:52
URI: http://orca.cf.ac.uk/id/eprint/120653

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