- Title
- Optimally parameterized wavelet packet transform for incipient machine fault diagnosis
- Creator
- Yaqub, Muhammad Farrukh; Gondal, Iqbal; Kamruzzaman, Joarder
- Date
- 2011
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/160871
- Identifier
- vital:12384
- Identifier
-
https://doi.org/10.1299/jsmelem.2011.6._3242-1_
- Abstract
- Vibration signals used for abnormality detection in machine health monitoring (MHM) are non-stationary in nature. Wavelet packet transform is extensively used in the literature for comprehensive analysis of non-stationary vibration signal but these techniques work only for a specific application lacking in some generalized methodology for selecting appropriate wavelet decomposition level and nodes for optimal performance. This study proposes a framework for inchoate fault detection by selecting the optimal wavelet decomposition level and nodes, named Optimally Parameterized Wavelet Packet Transform (OPWPT). OPWPT uses support vector machine to build the fault diagnostic model. Results in comparison with the existing schemes validate that OPWPT enhances the fault detection accuracy significantly in case of incipient faults when vibration signatures are very weak and overall signal to noise ratio is very poor.
- Relation
- 6th International Conference on Leading Edge Manufacturing in 21st Century, LEM 2011
- Rights
- © 2011 The Japan Society of Mechanical Engineers
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0910 Manufacturing Engineering; 0913 Mechanical Engineering; Machine health monitoring; Bearing faults; Wavelet level selection; Wavelet node selection
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