Development of an online condition monitoring system for slow speed machinery
Kim, Eric, Tan, Andy, Mathew, Joseph, & Yang, Bo-Suk (2010) Development of an online condition monitoring system for slow speed machinery. In Kiritsis, Dimitris, Emmanouilidis, Christos, Koronios, Andy, & Mathew, Joseph (Eds.) Proceedings of the 4th World Congress of Engineering Assets Management (WCEAM 2009), Springer-Verlag London Ltd, Ledra Marriott Hotel, Athens.
One of the main challenges of slow speed machinery condition monitoring is that the energy generated from an incipient defect is too weak to be detected by traditional vibration measurements due to its low impact energy. Acoustic emission (AE) measurement is an alternative for this as it has the ability to detect crack initiations or rubbing between moving surfaces. However, AE measurement requires high sampling frequency and consequently huge amount of data are obtained to be processed. It also requires expensive hardware to capture those data, storage and involves signal processing techniques to retrieve valuable information on the state of the machine. AE signal has been utilised for early detection of defects in bearings and gears. This paper presents an online condition monitoring (CM) system for slow speed machinery, which attempts to overcome those challenges. The system incorporates relevant signal processing techniques for slow speed CM which include noise removal techniques to enhance the signal-to-noise and peak-holding down sampling to reduce the burden of massive data handling. The analysis software works under Labview environment, which enables online remote control of data acquisition, real-time analysis, offline analysis and diagnostic trending. The system has been fully implemented on a site machine and contributing significantly to improve the maintenance efficiency and provide a safer and reliable operation.
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|Item Type:||Conference Paper|
|Keywords:||Condition Monitoring, Diagnosis, Prognosis, Low Speed|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300) > Automation and Control Engineering (091302)|
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300) > Mechanical Engineering not elsewhere classified (091399)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering|
Past > Schools > School of Engineering Systems
|Copyright Owner:||Copyright 2010 Springer-Verlag London Ltd.|
|Copyright Statement:||This is the author-version of the work. Conference proceedings published by Springer Verlag will be available via SpringerLink. http://www.springerlink.com|
|Deposited On:||21 Mar 2011 09:48|
|Last Modified:||29 Feb 2012 23:59|
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