Generic Self Repair Architecture with On-Line Fault Diagnosis

Author(s):  
Stefan Kristofik ◽  
Marcel Balaz ◽  
Maria Fischerova
Keyword(s):  
On Line ◽  
Author(s):  
Mariagrazia Dotoli ◽  
Maria P. Fanti ◽  
Agostino M. Mangini ◽  
Walter Ukovich

2005 ◽  
Vol 293-294 ◽  
pp. 365-372 ◽  
Author(s):  
Yong Yong He ◽  
Wen Xiu Lu ◽  
Fu Lei Chu

The steam turboset is the key equipment of the electric power system. Thus, it is very important and necessary to monitor and diagnose the running condition and the faults of the steam turboset for the safe and normal running of the electric power system. In this paper, the Internet/Intranet based remote condition monitoring and fault diagnosis scheme is proposed. The corresponding technique and methods are discussed in detail. And a real application system is developed for the 300MW steam turboset. In this scheme, the system is built on the Internet/Intranet and the Client/Server construction and Web/Server model are adopted. The proposed scheme can guarantee real-time data acquisition and on-line condition analysis simultaneously. And especially, the remote condition monitoring and fault diagnosis can be implemented effectively. The developed system has been installed in a power plant of China. And the plant has obtained great economic benefits from it.


2012 ◽  
Vol 548 ◽  
pp. 544-547
Author(s):  
Yong Zhi Liu ◽  
Cong Liu

A new method of fault diagnosis on the rotating rectifier of aeronautic synchronous is raised in the work. Firstly, the condition, truth and approach of EMD are introduced, and the method and steps of building up the feature vector are also included, Secondly the theories of LS-SVM and the arithmetic in the classification are also included. Finally taking the faults of one and two diodes turning off for example, after extracting the feature vector of exciting current based on EMD and establishing the classifying method based on Gauss RBF LS-SVM, the test, analysis and comparison can be on between LS-SVM and NN the conclusion can be got that the classified method referred in the work owns higher exactness, takes less time and has more application on the on-line fault diagnosis NN.


2010 ◽  
Vol 49 (4) ◽  
pp. 587-595 ◽  
Author(s):  
K. Renganathan ◽  
Vidhyacharan Bhaskar

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