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EMD, Ranking Mutual Information and PCA Based Condition Monitoring

[+] Author Affiliations
Xiaomin Zhao, Ming J. Zuo, Tejas Patel

University of Alberta, Edmonton, AB, Canada

Paper No. DETC2010-29126, pp. 777-782; 6 pages
doi:10.1115/DETC2010-29126
From:
  • ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 5: 22nd International Conference on Design Theory and Methodology; Special Conference on Mechanical Vibration and Noise
  • Montreal, Quebec, Canada, August 15–18, 2010
  • Conference Sponsors: Design Engineering Division and Computers in Engineering Division
  • ISBN: 978-0-7918-4413-7 | eISBN: 978-0-7918-3881-5
  • Copyright © 2010 by ASME

abstract

Success of any health monitoring system chiefly relies on the effectiveness of condition monitoring parameter. The parameter could be a single or combination of many vibration features. These features are expected to have a monotonic trend with the damage/fault progression. Ranking mutual information technique has the ability to detect the features that have monotonic trend and PCA is a popular and widely accepted multidimensional analysis tool for the feature fusion. A condition monitoring method is presented in this paper by combining EMD, ranking mutual information and PCA. The proposed method is helpful in generation of the indicator that represents the damage progression. This method is tested on the impeller health condition monitoring of a pump.

Copyright © 2010 by ASME

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