Development of an Online Condition Monitoring System for Slow Speed Machinery
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.
KeywordsAcoustic Emission Acoustic Emission Signal Acoustic Emission Event Outer Race Acoustic Emission Sensor
Unable to display preview. Download preview PDF.
- 4.Alfredson AC & Mathew J. (1985) Time domain methods for monitoring the condition of rolling element bearings. Mechanical Engineering Transactions.Google Scholar
- 9.Rao RBKN. Advances in acoustic emission technology (AET) in COMADEM: A state-of-the-art review, COMADEM2003, 1-18.Google Scholar
- 11.Tandon N & Nakra BC. (1999) Defect detection in rolling element bearings by acoustic emission method, Journal of Acoustic Emission, 9(1), 25-28.Google Scholar
- 13.Jamuludin N, Mba D & Bannister RH. (2001) Condition monitoring of slow-speed rolling element bearings using stress waves, In Proceedings of the IMechE, 215(4), pp. 245-271, ProQuest Science Journal.Google Scholar
- 15.Kim Y-H, Tan ACC, Mathew J & Yang B-S. (2006) Condition monitoring of low speed bearings: a comparative study of the ultrasound technique versus vibration measurement, In WCEAM’06, World congress on engineering asset management, paper no. 26, Gold coast, Springer Publisher.Google Scholar
- 16.Kim Y-H, Tan ACC, Mathew J, Kosse V & Yang B-S. (2007) A comparative study on the application of acoustic emission technique and acceleration measurements for low speed condition monitoring, In APVC’07, Asiapacific vibration conference, Sapporo.Google Scholar
- 17.Kim EY, Tan A & Yang B-S (2008) Fault detection of slow speed rolling element bearing with noise removal techniques, In 15th ICSV, International Congress on Sound and Vibration, pp. 1981-1988, Daejeon,Google Scholar