A hybrid framework combining data-driven and model-based methods for system remaining useful life prediction

2016 ◽  
Vol 44 ◽  
pp. 191-199 ◽  
Author(s):  
Linxia Liao ◽  
Felix Köttig
Author(s):  
Naipeng Li ◽  
Yaguo Lei ◽  
Nagi Gebraeel ◽  
Zhijian Wang ◽  
Xiao Cai ◽  
...  

2021 ◽  
Vol 11 (18) ◽  
pp. 8482
Author(s):  
Jie Li ◽  
Yuejin Tan ◽  
Bingfeng Ge ◽  
Hua Zhao ◽  
Xin Lu

This paper proposes a method on predicting the remaining useful life (RUL) of a concrete piston of a concrete pump truck based on probability statistics and data-driven approaches. Firstly, the average useful life of the concrete piston is determined by probability distribution fitting using actual life data. Secondly, according to condition monitoring data of the concrete pump truck, a concept of life coefficient of the concrete piston is proposed to represent the influence of the loading condition on the actual useful life of individual concrete pistons, and different regression models are established to predict the RUL of the concrete pistons. Finally, according to the prediction result of the concrete piston at different life stages, a replacement warning point is established to provide support for the inventory management and replacement plan of the concrete piston.


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