@inproceedings{c52e7f347781432dbbd605c4741670c1,
title = "Real-time reliability prediction for wind turbines speed control systems based on sensor fault prediction",
abstract = "Failure of wind turbines often has a devastating impact on the wind power industry. This is because the cost of maintenance when the wind turbine has a failure is much bigger the cost of maintenance when wind turbines have not failed. Failure in this wind turbine can be minimized by knowing the reliability of wind turbines in real-time. This paper presents a new real-time reliability prediction for wind turbines which incorporates a sensor fault prediction algorithm. The two steps need to be done are observer design and reliability prediction algorithm. The observer test is to calculate n-step sensor fault prediction for exponential smoothing algorithm, then the reliability prediction is conducted based on the sensor fault prediction result. This fault prediction result directly is used to predict real-time reliability. Based on the simulation results show that real-time reliability prediction has been successfully implemented on the wind turbines speed control systems.",
author = "Lilik Ayurani and Katherin Indriawati",
note = "Publisher Copyright: {\textcopyright} 2019 American Institute of Physics Inc. All rights reserved.; 2nd Engineering Physics International Conference 2018, EPIC 2018 ; Conference date: 31-10-2018 Through 02-11-2018",
year = "2019",
month = mar,
day = "29",
doi = "10.1063/1.5095271",
language = "English",
series = "AIP Conference Proceedings",
publisher = "American Institute of Physics Inc.",
editor = "Hatta, {Agus Muhamad} and Katherin Indriawati and Gunawan Nugroho and Biyanto, {Totok Ruki} and Dhany Arifianto and Risanti, {Doty Dewi} and Sonny Irawan",
booktitle = "Advanced Industrial Technology in Engineering Physics",
}