QUT ePrints

Experimental study on condition monitoring of low speed bearings : time domain analysis

Kim, Eric Y., Tan, Andy C.C., Yang, Bo-Suk , & Kosse, Vladis (2007) Experimental study on condition monitoring of low speed bearings : time domain analysis. In Albermani, Faris (Ed.) Fifth Australasian Congress on Applied Mechanics (ACAM 2007), 10–12 December, 2007, Brisbane, Australia.

Abstract

In condition monitoring of low speed rolling element bearings (REBs), traditional techniques involving vibration acceleration may not be able to detect a growing fault due to the low impact energy generated by the relative motion of the components. This study presents an experimental evaluation for incipient fault detection of low speed REBs by using an acoustic emission (AE) sensor and an accelerometer. A low speed fault simulation test rig was developed to simulate common machine faults with shaft speeds as low as 10rpm under loading conditions. Tests were conducted on the rig with various seeded defect bearings. This study reveals the best frequency bandwidth and suitable parameters for condition monitoring using AE signal for early detection of low speed bearing defects by means of statistical parameters in time domain.

Impact and interest:

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 14425
Item Type: Conference Paper
Additional Information: The contents of this paper can be freely accessed online via the URL page provided(see hypertext link).
Additional URLs:
ISBN: 0858258625
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300) > Mechanical Engineering not elsewhere classified (091399)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2007 Engineers Australia
Deposited On: 19 Aug 2008
Last Modified: 29 Feb 2012 23:38

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page