An integrated Gaussian process regression for prediction of remaining useful life of slow speed bearings based on acoustic emission
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- 作者：S.A. Aye ; Sylvester.Aye@up.ac.za" class="auth_mail" title="E-mail the corresponding author ; sylvester.a.aye@gmail.com" class="auth_mail" title="E-mail the corresponding author ; P.S. Heyns Stephan.Heyns@up.ac.za" class="auth_mail" title="E-mail the corresponding author
- 关键词：Gaussian process regressions ; Remaining useful life ; Mean function ; Covariance function
- 刊名：Mechanical Systems and Signal Processing
- 出版年：2017
- 出版时间：1 February 2017
- 年：2017
- 卷：84
- 期：part_PA
- 页码：485-498
- 全文大小：1843 K
文摘
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An optimal GPR for prediction of RUL was proposed.
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Integration of simple mean and covariance functions.
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The findings show the resulting integrated GPR improves over simple GPR models.
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The integrated GPR predicts RUL with small errors.
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The findings are robust under varying operating conditions.