Lai, Jun JieJun JieLaiPan, Shih JieShih JiePanOng, Chong WeiChong WeiOngCHENG-LIANG CHEN2023-05-222023-05-222022-01-01978032385159615707946https://scholars.lib.ntu.edu.tw/handle/123456789/631289In this work, a scenario-based approach that uses multiple Weibull Accelerated Failure Time Regression (WAFTR) models is proposed to predict the remaining useful life (RUL) of a benchmark bearing. The external features such as operational load and rotatory speed of the bearing are used to categorize the operational scenarios and a scenario-based WAFTR model is identified for each operational scenario by using the internal features extracted from the sampled horizontal and vertical vibration data. Therein, the Weibull parameters in each WAFTR model are expressed either in exponential or in linear form of these internal and external operational features. By using the mean squared error (MSE) as the performance measure of the prediction model, it is found that the proposed multiple WAFTR models approach can predict the RUL within 20% error.Bearing | Reliability function | Remaining Useful Life (RUL) | Weibull distributionbook part10.1016/B978-0-323-85159-6.50138-X2-s2.0-85136302318https://api.elsevier.com/content/abstract/scopus_id/85136302318