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Fault Signal Extraction Using Deviation Energy in Frequency Domain

Shi, John Z., Higson, Andrew, Kidd, Moray, Gu, Fengshou and Ball, Andrew (2007) Fault Signal Extraction Using Deviation Energy in Frequency Domain. In: Second World Congress on Engineering Asset Management and the Fourth International Conference on Condition Monitoring, 11-14 June 2007, Harrogate, UK.

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Abstract

This paper proposed a new method for fault signal extraction from a mixture vibration or acoustic signal with single measurement. This method is based on the fact that an occasionally happened fault brings additional frequency components and additional energy into the process and the additional frequency components can be extracted by examining their changing ratio in the frequency domain. Because the stochastic process is involved, this paper starts with the discussion of stochastic processing. After that, the deviation ratio and deviation energy are defined by extending the notion of variation coefficient. The deviation energy method is then developed and presented immediately by cross transformation between the frequency domain and time domain. In the frequency domain, relative comparison of normal components and abnormal components are separated by the calculation of deviation energy, whereas the index of segment in the stochastic process is taken and used for time domain signal extraction. To prove the effectiveness of this method, some case studies are conducted using complicated acoustics signals from car cabin with random driving. A conclusion is drawn that the deviation energy method is effective in fault signal extraction and separation.

Item Type: Conference or Workshop Item (Keynote)
Additional Information: Two global events on Engineering Asset Management and Condition Monitoring hit the United Kingdom… 4 January 2007: The United Kingdom will host two global events: the Second World Congress on Engineering Asset Management and the Fourth International Conference on Condition Monitoring on the 11th - 14th June 2007, at the Cairn Hotel, Harrogate, Yorkshire UK.
Subjects: T Technology > TL Motor vehicles. Aeronautics. Astronautics
Schools: School of Computing and Engineering
School of Computing and Engineering > Automotive Engineering Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering > Diagnostic Engineering Research Centre > Energy, Emissions and the Environment Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Machinery Condition and Performance Monitoring Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
School of Computing and Engineering > High-Performance Intelligent Computing
School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
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Depositing User: Zhanqun Shi
Date Deposited: 18 Jun 2009 11:20
Last Modified: 08 Dec 2010 13:25
URI: http://eprints.hud.ac.uk/id/eprint/4358

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