Fault detection and isolation for a wind turbine benchmark using a mixed Bayesian/Set-membership approach

Fault Detection and Isolation for Continuous-time Switched Linear Systems: A Set Membership Approach

2020 17th International Multi-Conference on Systems, Signals & Devices (SSD) ◽

10.1109/ssd49366.2020.9364097 ◽

2020 ◽

Author(s):

Haifa Ethabet ◽

Tarek Raissi ◽

Messaoud Amairi ◽

Mohamed Aoun

Keyword(s):

Fault Detection ◽

Linear Systems ◽

Continuous Time ◽

Switched Linear Systems ◽

Extreme learning machine for fault detection and isolation in wind turbine

2016 International Conference on Electrical and Information Technologies (ICEIT) ◽

10.1109/eitech.2016.7519584 ◽

2016 ◽

Cited By ~ 2

Author(s):

Ayoub EL Bakri ◽

Miloud Koumir ◽

Ismail Boumhidi

Keyword(s):

Fault Detection ◽

Wind Turbine ◽

Extreme Learning Machine ◽

Learning Machine

A robust fault detection and isolation filter for a horizontal axis variable speed wind turbine

2013 American Control Conference ◽

10.1109/acc.2013.6580526 ◽

2013 ◽

Cited By ~ 4

Author(s):

B. Svetozarevic ◽

P. Mohajerin Esfahani ◽

M. Kamgarpour ◽

J. Lygeros

Keyword(s):

Fault Detection ◽

Wind Turbine ◽

Horizontal Axis ◽

Variable Speed ◽

Robust Fault Detection ◽

Variable Speed Wind Turbine

Sensor fault detection and isolation for a wireless sensor network-based remote wind turbine condition monitoring system

2017 IEEE Industry Applications Society Annual Meeting ◽

10.1109/ias.2017.8101845 ◽

2017 ◽

Cited By ~ 2

Author(s):

Yayu Peng ◽

Wei Qiao ◽

Liyan Qu ◽

Jun Wang

Keyword(s):

Wireless Sensor Network ◽

Fault Detection ◽

Wind Turbine ◽

Sensor Network ◽

Condition Monitoring ◽

Wireless Sensor ◽

Sensor Fault ◽

Sensor Fault Detection ◽

Condition Monitoring System

Causal fault detection and isolation based on a set-membership approach☆

Automatica ◽

10.1016/s0005-1098(04)00196-7 ◽

2004 ◽

Vol 40 (12) ◽

pp. 2099-2110 ◽

Cited By ~ 15

Author(s):

I FAGARASAN ◽

S PLOIX ◽

S GENTIL

Keyword(s):

Fault Detection ◽

Model-based Fault Detection and Isolation for V47/660kW wind turbine

2015 23rd Iranian Conference on Electrical Engineering ◽

10.1109/iraniancee.2015.7146470 ◽

2015 ◽

Cited By ~ 1

Author(s):

Shadi Asgari ◽

Alireza Yazdizadeh ◽

Mohammad G. Kazemi ◽

Mehrnoosh Kamarzarrin

Keyword(s):

Fault Detection ◽

Wind Turbine ◽

Model Based

Set-membership methodology for multiple fault detection and isolation in DC-DC Buck Converters

2016 18th Mediterranean Electrotechnical Conference (MELECON) ◽

10.1109/melcon.2016.7495377 ◽

2016 ◽

Author(s):

Rihab El Houda Thabet ◽

Houcine Chafouk

Keyword(s):

Fault Detection ◽

Buck Converters ◽

Multiple Fault ◽

A survey of fault detection and isolation in wind turbine drives

2013 International Conference on Power, Energy and Control (ICPEC) ◽

10.1109/icpec.2013.6527737 ◽

2013 ◽

Cited By ~ 3

Author(s):

R. S. Kumar ◽

M. Manimozhi ◽

M. T. Enosh

Keyword(s):

Fault Detection ◽

Wind Turbine ◽

Fault Detection And Isolation

Fault Detection and Isolation of a Benchmark Wind Turbine using the Likelihood Ratio Test

IFAC Proceedings Volumes ◽

10.3182/20110828-6-it-1002.03535 ◽

2011 ◽

Vol 44 (1) ◽

pp. 7079-7085 ◽

Cited By ~ 11

Author(s):

F. Kiasi ◽

J. Prakash ◽

S.L. Shah ◽

J.M. Lee

Keyword(s):

Fault Detection ◽

Wind Turbine ◽

Likelihood Ratio ◽

Likelihood Ratio Test ◽

Ratio Test

Extreme learning machine-based non-linear observer for fault detection and isolation of wind turbine

Australian Journal of Electrical & Electronics Engineering ◽

10.1080/1448837x.2019.1578044 ◽

2019 ◽

Vol 16 (1) ◽

pp. 12-20 ◽

Cited By ~ 4

Author(s):

Ayoub El Bakri ◽

Miloud Koumir ◽

Ismail Boumhidi

Keyword(s):

Fault Detection ◽

Wind Turbine ◽

Extreme Learning Machine ◽

Non Linear ◽

Linear Observer ◽

Learning Machine