Fault Diagnosis of Industrial Boiler Based on Competitive Agglomeration and Fuzzy Association Rules
Applying datamining algorithm to the association analyzes between the measurable parameters and faults in the industrial boiler control system. The works we have done generally as follows. According to the distribution of the parameters that can be measured, using competitive agglomeration clustering algorithm to partition the fuzzy interval of each attribute; based on the principle of association rules, an algorithm has been proposed to find the association between the parameters that can be measured and the fault; The proposed algorithm has been realized and validated. As the results proves that fault diagnosis of industrial boiler based on competitive agglomeration and fuzzy association rules can mining knowledge effectively, and the knowledge has higher correct rate than normal methods. The project was supported by National High-tech R&D Program (863 Program) (2007AA041401), Tianjin Natural Science Foundation (08JCZDJC18600, 09JCZDJC23900), and University Science and Technology Development Foundation of Tianjin (2006ZD32).
competitive agglomeration fuzzy association rules fault diagnosis industrial boiler
Zhao Hui Jiang Bi-bo Zhao Zhuo-qun
Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems, Tianjin University School of Electrical Engineering, Tianjin University of Technology, Tianjin, China School of Mechanical & Vehicle engineering, Hunan University,Changsha, China
国际会议
长春
英文
64-67
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）