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Data mining for fault diagnosis and machine learning for rotating machinery
Gang Zhao ; DongXiang Jiang ; Kai Li ; JinHui Diao
2010-05-11 ; 2010-05-11
关键词Practical Theoretical or Mathematical/ data mining diagnostic expert systems fault diagnosis learning (artificial intelligence) pattern classification steam power stations steam turbines vibrations/ rotating machinery machine learning database analyses data mining technique steam turbine fault diagnostics continuous data measurements classification rules standardized vibration frequency data/ B8230E Steam power stations and plants C7410B Power engineering computing C6130 Data handling techniques C1250 Pattern recognition C6170K Knowledge engineering techniques
中文摘要Data mining is used not only for database analyses, but also for machine learning. The data mining technique described in this paper was used for steam turbine fault diagnostics based on continuous data measurements. The classification rules are based on standardized vibration frequency data for steam turbines and field experts' analyses of turbine vibration problems. The expert knowledge enables the steam turbine fault diagnosis system to be more powerful and accurate. The system can identify twenty types of standard steam turbine faults. The system was developed using 2000 simulated data sets. The data mining methods were then used to identify 20 explicit rules for the turbine faults. The method was also used with actual power plant data to successfully diagnose real faults. The results indicate that data mining can be effectively applied to diagnosis of rotating machinery by giving useful rules to interpret the data.
语种英语 ; 英语
出版者Trans Tech Publications ; Switzerland
内容类型期刊论文
源URL[http://hdl.handle.net/123456789/25887]  
专题清华大学
推荐引用方式
GB/T 7714
Gang Zhao,DongXiang Jiang,Kai Li,et al. Data mining for fault diagnosis and machine learning for rotating machinery[J],2010, 2010.
APA Gang Zhao,DongXiang Jiang,Kai Li,&JinHui Diao.(2010).Data mining for fault diagnosis and machine learning for rotating machinery..
MLA Gang Zhao,et al."Data mining for fault diagnosis and machine learning for rotating machinery".(2010).
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