TY - GEN
T1 - Power plant fault monitoring using Recursive Principal Component Analysis RPCA
AU - Sánchez, Alberto
AU - Redrobán, Mauricio
AU - Aguirre, Omar
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/23
Y1 - 2017/1/23
N2 - Recursive Principal Components Analysis is explored as a method to identify and classify fault sources in a 12MW steam dual fuel power plant. The algorithm assessment is performed off-line by using data of relevant plant wide-information. A simple contributions matrix based in normalized data is proposed to diagnose plant faults. Results indicate it is possible to detect, classify and possibly even predict sources of plant failure.
AB - Recursive Principal Components Analysis is explored as a method to identify and classify fault sources in a 12MW steam dual fuel power plant. The algorithm assessment is performed off-line by using data of relevant plant wide-information. A simple contributions matrix based in normalized data is proposed to diagnose plant faults. Results indicate it is possible to detect, classify and possibly even predict sources of plant failure.
UR - http://www.scopus.com/inward/record.url?scp=85013827575&partnerID=8YFLogxK
U2 - 10.1109/ROPEC.2016.7830609
DO - 10.1109/ROPEC.2016.7830609
M3 - Contribución a la conferencia
AN - SCOPUS:85013827575
T3 - 2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016
BT - 2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016
Y2 - 9 November 2016 through 11 November 2016
ER -