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- W2140041591 abstract "The Remaining Useful Life(RUL) prediction of the equipment plays a significant role in maintenance management. The accurate RUL prediction based on the current and previous health condition of the equipment is essential to make a timely maintenance decision for failure avoidance. In this paper, we presented a novel RUL forecasting method of Proportional Hazards Model(PHM) assembled with Support Vector Machine(SVM). In this method, we employed SVM to identify abnormal data and regress raw data. A case study is presented, and the performances of RUL prediction of PHM and SVN-PHM are examined." @default.
- W2140041591 created "2016-06-24" @default.
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- W2140041591 date "2010-08-01" @default.
- W2140041591 modified "2023-09-23" @default.
- W2140041591 title "SVM-PHM: A Novel Method for Remaining Useful Life Prediction" @default.
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- W2140041591 doi "https://doi.org/10.1109/isme.2010.214" @default.
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