A multivariate grey RBF hybrid model for residual useful life prediction of industrial equipment based on state data. (2016)

• Record Type: Journal Article
• Authors: Chen, Xiaoshuang; Xiao, Hui; Guo, Yejun; Kang, Qi
• Is Part Of: International journal of wireless and mobile computing. Volume 10:Number 1(2016)
• Page Start: 90
• Page End: 96
• Publication Date: 2016
• Subjects: multivariate grey modelling -- RBF neural networks -- state data -- residual useful life forecasting -- performance degradation -- industrial equipment -- equipment lifetime; Mobile computing -- Periodicals; Wireless communication systems -- Periodicals; 004.6
• Languages: English
• ISSNs: 1741-1084

Abstract

In order to enhance the prediction precision of performance degradation characteristic parameters, we consider the condition parameters. This paper proposes an improved hybrid model named MVG+RBF which combines multivariate grey model and neural network. This hybrid model has the advantages of both grey model and RBF neural network. Based on the definition of residual useful life (RUL), this paper also gives a forecast model of RUL. Finally, through a case study, we can draw a conclusion that the MVG+RBF model has a better prediction ability and a lower relative error than the traditional MVG model. The proposed model MVG+RBF also has extensive application.