COMPARISON OF ANNS AND DATA MINING METHODS ON AERO-ENGINES VIBRATION FAULT DIAGNOSIS
Being of Artificial Intelligent (AI) methods, Artificial Neural Networks (ANNs) and Data Mining have been extensively applied on machinery fault diagnosis. Aero-engine,as one kind of rotating machine with complex structure and high rotating speed, has complicated vibration faults. ANNs are ideal tools for aero-engine fault diagnosis, since they have strong ability to learn complex nonlinear functions. Data mining, another AI method, has advantages of discovering knowledge from mountain of data, providing a simple way to interpret complex decision problem, and automatically extract diagnostic rules to replace the experts advice. This paper presents application of the two AI methods on aero-engine vibration fault diagnosis and then makes a comparison between them. From the study of this paper, we can draw the conclusion that both the two ANN methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality.
Aero-engines vibration fault diagnosis artificial intelligent
Kai Xiong Dongxiang Jiang Kai Li Yongshan Ding
Department of Thermal Engineering, Tsinghua University Beijing 100084,China
国际会议
昆明
英文
228-233
2006-09-18（万方平台首次上网日期，不代表论文的发表时间）