THERMAL SCIENCE

International Scientific Journal

Indhu Ramalingam

,

Sankaran Rangasamy Annamalai

,

Sugumaran Vaithiyanathan

FAULT DIAGNOSIS OF WIND TURBINE BEARING USING WIRELESS SENSOR NETWORKS

ABSTRACT
This paper proposes wireless sensor networks to monitor the condition of wind turbines. It addresses lifetime maximization issue of sensor nodes using stable election protocol for a cluster of up to nine wind turbines. This paper presents results of both experimental and simulation studies of a wind turbine plant, in which the vibration signals from each wind turbine are taken and with the help of machine learning technique, the fault diagnosis is done for a plant with wireless sensor networks. An experimental case study is performed from a wireless sensor networks with a well reported wind turbine bearing fault diagnosis data set. The outcome of the study shows that if the number of wind turbines is five for one base station, then the lifetime of the sensor nodes are maximum using MATLAB.
KEYWORDS
fault diagnosis, wind turbines, wireless sensor networks, life time maximization
PAPER SUBMITTED: 2017-03-20
PAPER REVISED: 2017-05-25
PAPER ACCEPTED: 2017-06-13
PUBLISHED ONLINE: 2017-12-16
DOI REFERENCE: https://doi.org/10.2298/TSCI17S2523R
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2017, VOLUME 21, ISSUE Supplement 2, PAGES [S523 - S531]
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FAULT DIAGNOSIS OF WIND TURBINE BEARING USING WIRELESS SENSOR NETWORKS

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence