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Reseach Article

Wavelet based Fault Detection for Wind Turbine

Published on October 2011 by Dinesh Kumar J, Harikrishan.N, Karuppiah.S, Manoj.N, Satish S, Vishal.L, Sunil Nag.P.V
International Symposium on Devices MEMS, Intelligent Systems & Communication
Foundation of Computer Science USA
ISDMISC - Number 8
October 2011
Authors: Dinesh Kumar J, Harikrishan.N, Karuppiah.S, Manoj.N, Satish S, Vishal.L, Sunil Nag.P.V
f84b170b-1de4-4b3c-807e-16db79905f9b

Dinesh Kumar J, Harikrishan.N, Karuppiah.S, Manoj.N, Satish S, Vishal.L, Sunil Nag.P.V . Wavelet based Fault Detection for Wind Turbine. International Symposium on Devices MEMS, Intelligent Systems & Communication. ISDMISC, 8 (October 2011), 7-10.

@article{
author = { Dinesh Kumar J, Harikrishan.N, Karuppiah.S, Manoj.N, Satish S, Vishal.L, Sunil Nag.P.V },
title = { Wavelet based Fault Detection for Wind Turbine },
journal = { International Symposium on Devices MEMS, Intelligent Systems & Communication },
issue_date = { October 2011 },
volume = { ISDMISC },
number = { 8 },
month = { October },
year = { 2011 },
issn = 0975-8887,
pages = { 7-10 },
numpages = 4,
url = { /proceedings/isdmisc/number8/3772-isdm161/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Symposium on Devices MEMS, Intelligent Systems & Communication
%A Dinesh Kumar J
%A Harikrishan.N
%A Karuppiah.S
%A Manoj.N
%A Satish S
%A Vishal.L
%A Sunil Nag.P.V
%T Wavelet based Fault Detection for Wind Turbine
%J International Symposium on Devices MEMS, Intelligent Systems & Communication
%@ 0975-8887
%V ISDMISC
%N 8
%P 7-10
%D 2011
%I International Journal of Computer Applications
Abstract

Renewable energy sources are gaining high prominence in today’s world. However, these sources do not supply energy throughout the year and hence efficiency is required when extracting energy from them. Wind energy is a recently developing area of common interest. Efficiency of a wind turbine is however, very low. Hence, detection of fault in the system becomes very essential so as to increase the efficiency. Fault detection is the primary step in FDI (Fault Detection and Isolation) and hence has to be executed using methods giving highest accuracy in predicting the occurrence of a fault. Wavelet transformation is a method which is used to separate the output signal from the faulty signals. Executing wavelet transformation for various sub-systems in the wind turbine, faults in different sub-systems can be detected. Here, we have used a benchmark model for the wind turbine and we have attempted to show how wavelet transform can be used to detect faults.

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Index Terms

Computer Science
Information Sciences

Keywords

Wind Turbine Fault Wavelet. SVM piezoelectric accelerometer