Ma, Xiandong (2011) Online intelligent condition monitoring of electrical machines. In: The 24th International Congress on Condition Monitoring and Diagnostics Engineering Management (COMADEM2011), 2011-05-302011-06-01.
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Condition monitoring needs smart technologies to diagnose faults and prognose failures, which this paper will investigate. The paper starts with the description of the fundamentals of system identification and neural network approaches. The proposed models will be tested and validated with measurement data. Issues related specially to continuous online monitoring will be addressed for these models. The work demonstrates that the proposed techniques can be potentially applied to online condition monitoring and therefore health assessment of power plant generators.
|Item Type:||Conference or Workshop Item (Paper)|
|Journal or Publication Title:||The 24th International Congress on Condition Monitoring and Diagnostics Engineering Management (COMADEM2011)|
|Additional Information:||Conference name: The 24th International Congress on Condition Monitoring and Diagnostics Engineering Management (COMADEM2011), Stavanger, Norway, 30th May - 1st June 2011|
|Uncontrolled Keywords:||System identification ; artificial neural network (ANN) ; condition monitoring ; generator ; power plant|
|Subjects:||T Technology > TA Engineering (General). Civil engineering (General)|
T Technology > TK Electrical engineering. Electronics Nuclear engineering
|Departments:||Faculty of Science and Technology > Engineering|
|Deposited By:||Dr Xiandong Ma|
|Deposited On:||24 May 2011 13:36|
|Last Modified:||29 Apr 2017 00:09|
Available Versions of this Item
- Online intelligent generator condition monitoring. (deposited 14 Dec 2010 08:44)
- Online intelligent condition monitoring of electrical machines. (deposited 24 May 2011 13:36)[Currently Displayed]
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