Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review
Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review
}
TY - CONF
T1 - Online intelligent condition monitoring of electrical machines.
AU - Ma, Xiandong
N1 - Conference name: The 24th International Congress on Condition Monitoring and Diagnostics Engineering Management (COMADEM2011), Stavanger, Norway, 30th May - 1st June 2011
PY - 2011/5
Y1 - 2011/5
N2 - 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.
AB - 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.
KW - System identification
KW - artificial neural network (ANN)
KW - condition monitoring
KW - generator
KW - power plant
M3 - Conference paper
SP - 223
EP - 228
T2 - The 24th International Congress on Condition Monitoring and Diagnostics Engineering Management (COMADEM2011)
Y2 - 30 May 2011 through 1 June 2011
ER -