A method for predicting the remaining life of equipment based on WTTE-CNN-LSTM

A method for predicting the remaining life of equipment based on WTTE-CNN-LSTM

At present, the uncertainty and randomness between equipment are not fully considered in the remaining useful life (RUL) prediction. In order to solve this problem, firstly, we use the Weibull distribution to describe the influence of various uncertain factors on the RUL of equipment, and introduce...

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Bibliographic Details
Main Authors: Erbao XU, Yan LI, Zhoupeng HAN, Jingyi DU, Mingshun YANG, Xinqin GAO
Format: Article
Language:English
Published: The Japan Society of Mechanical Engineers 2022-01-01
Series:Journal of Advanced Mechanical Design, Systems, and Manufacturing
Subjects:
remaining useful life prediction(rul)
weibull time-to-event recurrent neural network (wtte-rnn)
convolutional neural network (cnn)
long-short term memory (lstm)
Online Access:https://www.jstage.jst.go.jp/article/jamdsm/16/1/16_2022jamdsm0001/_pdf/-char/en

Internet

https://www.jstage.jst.go.jp/article/jamdsm/16/1/16_2022jamdsm0001/_pdf/-char/en

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