Grey rough sets hybrid scheme for intelligent fault diagnosis
Wei Jiang, Xiaoqiang Zhong, Jiyang Qi, Changan Zhu · 2007
This paper introduces a hybrid scheme that combines the advantages of grey relation analysis and rough sets for fault diagnosis. The introduced scheme starts with reduce superfluous attributes and quantitatively determine the relative importance of the attributes, and then grey correlation analysis is used to calculate the grey correlation degree of all the standard fault states with respect to the current state according to reduced attributes and their relative importance, so that the fault can be found. We develop a graphical user interface of the prototype based on Matlab7.1 to test the proposed method. The experimental results show that the hybrid scheme applied in this study performs well and lays the foundation for the intelligent fault diagnosis.