Publications

@conference{Chouiref2015199,

title = {Subspace identification based scheme for Fault Detection in drive train system},

author = {H. Chouiref and B. Boussaid and M. N. Abdelkrim and V. Puig and C. Abrun},

editor = {Chaabane M. Aitouch A. Mehdi D.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962579333\&doi=10.1109%2fICoSC.2015.7152787\&partnerID=40\&md5=5061bceff954d6c9e226d8089cc46f0c},

doi = {10.1109/ICoSC.2015.7152787},

isbn = {9781479983186},

year  = {2015},

date = {2015-01-01},

journal = {2015 4th International Conference on Systems and Control, ICSC 2015},

pages = {199-205},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {In order to improve reliability of wind turbines, it is important to detect faults as fast as possible. The fault introduced in this work is the dynamics change of the drive train due to the increased friction from its nominal value will be treated. For diagnosis purpose, a residual generation is used based on a comparison between the nominal generator speed and the observed one obtained by the use of the predictor based LPV subspace identification technique (LPV PBSID) applied at the benchmark system introduced in IFAC SAFEPROCESS 2009 which is modeled as an LPV model considering the wind speed as scheduling variable. © 2015 IEEE.},

note = {cited By 0},

keywords = {Benchmark system; Drive train; Generator speed; Nominal values; Residual generation; Scheduling variable; Subspace identification; Wind speed, Fault detection, Wind; Wind turbines},

pubstate = {published},

tppubtype = {conference}

}