A DESIGN OF AUTOMATIC FAULT DIAGNOSIS SYSTEM FOR ROTATING MACHINERY
Due to the growing standards in modern industry, the fault diagnosis system increasingly requires auto-inferring and intelligent. Thus, in this paper, several methods are discussed on auto-diagnosis system design: rough set, which effectively simplifies redundant information; rule-regularizing, which helps system realize self-illation and self-study; and fuzzy processing, which makes system more robust and adaptable. Integrated these methods into one system dramatically enhances voluntary process in diagnosis. In this way, an automatic fault diagnosis system for rotating machinery is established, which reduces space-time consumption, weakens human intervention, and accelerates diagnosis speed. The most important achievement of this project is that this system minimizes human-operating during the diagnosis process, which is supported by the experiments in the 3rd part of this paper.
Automatic Fault Diagnosis Rotating Machinery Rough Set Fuzzy Processing Rule-Regularized
Cao Xi Yuan Hong-Fang Liang Liang
Diagnosis and Self-recovery Engineering Research Center, Beijing University of Chemical Technology, Dept. of Information Science and Technology, Beijing University of Chemical Technology, Beijing 1000
国际会议
北京
英文
221-226
2008-10-27（万方平台首次上网日期，不代表论文的发表时间）