Acoustic emission condition monitoring : an application for wind turbine fault detection

Purarjomandlangrudi, Afrooz & Nourbakhsh, Ghavameddin (2013) Acoustic emission condition monitoring : an application for wind turbine fault detection. International Journal of Research in Engineering and Technology, 2(5), pp. 907-918.

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Abstract

Low speed rotating machines which are the most critical components in drive train of wind turbines are often menaced by several technical and environmental defects. These factors contribute to mount the economic requirement for Health Monitoring and Condition Monitoring of the systems. When a defect is happened in such system result in reduced energy loss rates from related process and due to it Condition Monitoring techniques that detecting energy loss are very difficult if not possible to use. However, in the case of Acoustic Emission (AE) technique this issue is partly overcome and is well suited for detecting very small energy release rates. Acoustic Emission (AE) as a technique is more than 50 years old and in this new technology the sounds associated with the failure of materials were detected. Acoustic wave is a non-stationary signal which can discover elastic stress waves in a failure component, capable of online monitoring, and is very sensitive to the fault diagnosis. In this paper the history and background of discovering and developing AE is discussed, different ages of developing AE which include Age of Enlightenment (1950-1967), Golden Age of AE (1967-1980), Period of Transition (1980-Present). In the next section the application of AE condition monitoring in machinery process and various systems that applied AE technique in their health monitoring is discussed. In the end an experimental result is proposed by QUT test rig which an outer race bearing fault was simulated to depict the sensitivity of AE for detecting incipient faults in low speed high frequency machine.

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ID Code: 68724
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Low speed rotating machine, Condition monitoring systems, Acoustic emission (AE)
ISSN: 2320-8791
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 IJRET
Deposited On: 19 Mar 2014 01:57
Last Modified: 19 Mar 2014 22:29

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