Research on Intelligent Fault Diagnosis Method Based on Rough Set Theory and Fuzzy Petri Nets

摘要：

Rough sets theory (RST) and Fuzzy Petri nets (FPN) have been widely used in fault diagnosis. However, RST has the weakness of over-rigidity decision, and FPN has the dimensional disaster problem. In order to solve these shortcomings, according to complementary strategy, a new fault diagnosis method based on integration of RST and FPN was presented. Firstly, RST was applied to remove redundant fault features and simply fault information, so that the minimal diagnostic rules can be obtained and the fault was roughly diagnosed. Secondly, the optimal FPN structure was built and the fault diagnosis was finally realized through matrix operation of FPN. Finally, a diesel engine fault diagnosis example was analyzed, and the results show that the proposed method not only holds the ability of RST for analyzing and reducing data, but also has the advantage of FPN for parallel reasoning, so it has strong engineering practicability and validity.

关键词： Fault Diagnosis Rough Set Fuzzy Petri Nets Matrix Operation Parallel Reasoning

作者: Lanyun Li Zhuanzhao Yang Zhi He

作者单位: Key Laboratory of Materials Processing Engineering, School of Materials Science and Engineering,Xia Tubular Goods Research Center of CNPC, Xian, Shaanxi, 710065 P.R.China

会议类型: 国际会议

会议名称: 2010 International Conference on Advanced Mechanical Engineering(2010年先进机械工程国际学术会议 AME 2010)

会议地点: 洛阳

会议语种:英文

页码: 77-82

在线出版日期: 2010-09-04（万方平台首次上网日期，不代表论文的发表时间）