Open Science Research Excellence
@article{(International Science Index):,
  title    = {Robust Fault Diagnosis for Wind Turbine Systems Subjected to Multi-Faults},
  author    = {Sarah Odofin and  Zhiwei Gao and  Sun Kai},
  country   = {United Kingdom},
  institution={Northumbria University},
  abstract  = {Operations, maintenance and reliability of wind
turbines have received much attention over the years due to the rapid
expansion of wind farms. This paper explores early fault diagnosis
technique for a 5MW wind turbine system subjected to multiple
faults, where genetic optimization algorithm is employed to make the
residual sensitive to the faults, but robust against disturbances. The
proposed technique has a potential to reduce the downtime mostly
caused by the breakdown of components and exploit the productivity
consistency by providing timely fault alarms. Simulation results show
the effectiveness of the robust fault detection methods used under
Matlab/Simulink/Gatool environment.
    journal   = {International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering},  volume    = {9},
  number    = {2},
  year      = {2015},
  pages     = {220 - 225},
  ee        = {},
  url       = {},
  bibsource = {},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 98, 2015},