DocumentCode :
1898825
Title :
Extraction Fault Rule of Rotation Equipment Based on Rough Set
Author :
Li Meng ; Shu Yunxing ; Mao Jiandong ; Li Xiaohua
Author_Institution :
Luoyang Inst. of Sci. & Technol., Luoyang, China
Volume :
2
fYear :
2009
fDate :
10-11 Oct. 2009
Firstpage :
604
Lastpage :
607
Abstract :
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.
Keywords :
failure (mechanical); fault diagnosis; machinery; mechanical engineering computing; rough set theory; data selection; extraction fault rule; mechanical failure; reduction method; rotation equipment fault diagnosis; rough set; vibration frequency; Data analysis; Data mining; Databases; Equipment failure; Failure analysis; Fault detection; Fault diagnosis; Filters; Frequency; Vibrations; fault rule; rotation equipmen; rought set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
Type :
conf
DOI :
10.1109/ICICTA.2009.380
Filename :
5287754
Link To Document :
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