Extraction Fault Rule of Rotation Equipment Based on Rough Set
Li Meng, Shu Yunxing, Mao Jian-dong, Xiaohua Li · 2009
In order to improve the accuracy of rotation equipment fault diagnosis, and be directed to the mechanical failure in the UCI database, the characteristics of detection parameter in the data set is analysed, no filter vertical amplitude, filter vertical vibration speed, and the key detection parameter of the rotating equipment failure is vibration frequency. As a result, the method which the data of rotation equipment failure is mined by rough set is proposed. In the data set, the data selection, discrete, establishment of decision-making table and reduction method are introduced. Expert system rule base of rotating equipment failure will be realized by extraction of rotating equipment fault rule.