Remaining Useful Life Prediction of the Concrete Piston Based on Probability Statistics and Data Driven

Abstract

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.

RUL Prediction of Rolling Bearings Based on a DCAE and CNN

“…Y. Qian et al applied the multi-time scale method to the prediction of the RUL of rolling bearings, established a multi-dimensional dynamic system based on phase space warping (PSW) technology and finally predicted the RUL of bearings successfully and quickly by combining the system with the improved Paris model [13]. Some researchers combined the physical model with the data-driven method based on deep learning and have achieved good results in RUL prediction for rolling bearings [14][15][16][17][18]. Through the current research results of scholars, it can be found that the main processes of the life analysis and prediction methods of mechanical equipment are data acquisition, degradation state modeling and RUL prediction.…”