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- W2043151330 abstract "The development of accurate health condition prediction approaches has been a key research topic in condition based maintenance (CBM) in recent years. However, current health condition prediction approaches are not accurate enough, which has become the bottleneck for achieving the full power of CBM. In this work, we develop a recurrent neural network approach for equipment health condition prediction. The effectiveness of the approach is illustrated using data collected from a lab gearbox experimental system." @default.
- W2043151330 created "2016-06-24" @default.
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- W2043151330 date "2009-01-01" @default.
- W2043151330 modified "2023-10-16" @default.
- W2043151330 title "Health condition prognostics of gears using a recurrent neural network approach" @default.
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- W2043151330 doi "https://doi.org/10.1109/rams.2009.4914720" @default.
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