General Fault Monitoring and Diagnosis Expert System Based on Fault Tree and Multi-sensor Information

摘要：

　　Due to the limited generality of traditional fault diagnosis expert system and its low accuracy of extracting failure symptoms,a general fault monitoring and diagnosis expert system has been built.For different devices,users can build fault trees in an interactive way and then the fault trees will be saved as expert knowledge.A variety of sensors are fixed to monitor the real-time condition of the device and intelligent algorithms such as wavelet transform and neural network are used to assist the extraction of failure symptoms.On the basis of integration of multi-sensor failure symptoms,the fault diagnosis is realized through forward and backward reasoning.The simulation diagnosis experiments of NC device have shown the effectiveness of the proposed method.

关键词： Fault diagnosis Expert system Fault tree Wavelet transform Neural network Forward and backward reasoning

作者: Aiyu Zhang Xiaoguang Zhao Lei Zhang

作者单位: State Key Laboratory of Intelligent Control and Management of Complex Systems, Institute ofAutomatio School of Control Science and Engineering, Shandong University, Jinan, Shandong,250061,China

会议类型: 国际会议

会议名称: the Second International Conference on Frontiers of Manufacturing and Design Science(第二届制造与设计科学国际会议(ICFMD 2011))

会议地点: 台湾

会议语种:英文

页码: 4481-4485

在线出版日期: 2011-12-11（万方平台首次上网日期，不代表论文的发表时间）