An expert system for fault diagnosis integrated in existing SCADA systems

Author(s):  
J.-P. Bernard ◽  
D. Durocher
2017 ◽  
Vol 11 (4) ◽  
pp. 270
Author(s):  
C. N. Tan ◽  
C. F. Tan ◽  
M. A. Abdullah

1984 ◽  
Vol 29 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Hiromitsu Kumamoto ◽  
Kenji Ikenchi ◽  
Koichi Inoue ◽  
Ernest J. Henley

2011 ◽  
Vol 121-126 ◽  
pp. 4481-4485
Author(s):  
Ai Yu Zhang ◽  
Xiao Guang Zhao ◽  
Lei Zhang

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.


2014 ◽  
Vol 945-949 ◽  
pp. 1707-1712
Author(s):  
Bin Shen ◽  
Shu Yu Zhao ◽  
Jia Hai Wang ◽  
Juergen Fleischer

Based on the authors previous work of developing an expert system for fault diagnosis of CNC machine tool, this paper studied the theory and method of CNC remote fault diagnosis expert system based on B/S, and presents schema and structure of the expert system in detailed. Case based reasoning is used for the multi-alarm diagnosis, and rule based reasoning is used for single-alarm diagnosis. At last fault diagnosis expert system was designed and developed making use of C# and ASP.NET.


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