Remining Useful Life Prediction of Equipment Driven by Multi-Sensor Data. Issue 5 (June 2019)

• Record Type: Journal Article
• Authors: Huijie, Zeng; Lin, Deng; Jiansheng, Guo; Jian, Wang; Tengjiao, Wang; Taoyong, Gu
• Is Part Of: Journal of physics. Volume 1213:Issue 5(2019)
• Publication Date: 2019-06
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1213/5/052005
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: This paper presents a method for predicting the remining useful life (RUL) of equipment by using multi-sensor monitoring data of equipment. Firstly, the performance degradation of equipment is evaluated based on the maximum information coefficient. Then the performance degradation model is built by using Wiener process with non-linear drift. The maximum likelihood is used to estimate the parameters of the model, and the probability density distribution of RUL considering random failure threshold is deduced. Finally, the parameters of the model are updated by improved particle filter, and the RUL of the remaining equipment is predicted.