A remote diagnosis system for rotating machinery using virtual reality

Author(s):  
M. Bellamine ◽  
N. Abe ◽  
K. Tanaka ◽  
Peng Chen ◽  
H. Taki



Author(s):  
Jiye Shao ◽  
Rixin Wang ◽  
Jingbo Gao ◽  
Minqiang Xu

The rotor is one of the most core components of the rotating machinery and its working states directly influence the working states of the whole rotating machinery. There exists much uncertainty in the field of fault diagnosis in the rotor system. This paper analyses the familiar faults of the rotor system and the corresponding faulty symptoms, then establishes the rotor’s Bayesian network model based on above information. A fault diagnosis system based on the Bayesian network model is developed. Using this model, the conditional probability of the fault happening is computed when the observation of the rotor is presented. Thus, the fault reason can be determined by these probabilities. The diagnosis system developed is used to diagnose the actual three faults of the rotor of the rotating machinery and the results prove the efficiency of the method proposed.







1998 ◽  
Vol 7 (1) ◽  
pp. 13-20
Author(s):  
Nobukazu Iguchi ◽  
Fumitaka Uchio ◽  
Takaharu Kameoka


2011 ◽  
Vol 201-203 ◽  
pp. 510-513
Author(s):  
Juan Li Li ◽  
Zhao Jian Yang

According to the data characteristics in the hoister operation process and the network requirements of fault diagnosis system, this paper proposes a XML-based apriori algorithm, and the algorithm is applied to hoist remote fault diagnosis system. The experiment result shows that applying the system can make the hoist fault diagnosis more scientific, reasonable and improve the efficiency and accuracy of diagnosis.



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