Prognosis of bearing failure based on health state estimation
Kim, Hack-Eun, Tan, Andy C. C., Mathew, Joseph, Kim, Eric Y. H., & Choi, Byeong-Keun (2009) Prognosis of bearing failure based on health state estimation. In Proceedings of the 4th World Congress on Engineering Asset Management, Springer, Marriott Athens Ledra Hotel, Athens.
This paper proposes a new prognosis model based on the technique for health state estimation of machines for accurate assessment of the remnant life. For the evaluation of health stages of machines, the Support Vector Machine (SVM) classifier was employed to obtain the probability of each health state. Two case studies involving bearing failures were used to validate the proposed model. Simulated bearing failure data and experimental data from an accelerated bearing test rig were used to train and test the model. The result obtained is very encouraging and shows that the proposed prognostic model produces promising results and has the potential to be used as an estimation tool for machine remnant life prediction.
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|Item Type:||Conference Paper|
|Keywords:||Prognosis, Bearing degradation state, Support vector machines, Remaining useful life|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300) > Mechanical Engineering not elsewhere classified (091399)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Artificial Intelligence and Image Processing not elsewhere classified (080199)
|Divisions:||Current > Research Centres > CRC Integrated Engineering Asset Management (CIEAM)
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
|Copyright Owner:||Copyright 2009 Springer|
|Copyright Statement:||The original publication is available at www.springerlink.com|
|Deposited On:||21 Oct 2009 05:22|
|Last Modified:||29 Feb 2012 13:59|
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