Publication Type:

Journal Article

Source:

IJCA Proceedings on International Symposium on Devices MEMS, Intelligent Systems & Communication (ISDMISC), IJCA Journal, Number 8, p.7-10 (2011)

URL:

http://www.ijcaonline.org/proceedings/isdmisc/number8/3772-isdm161

Keywords:

Fault, Wavelet. SVM piezoelectric accelerometer, wind turbine

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.

Cite this Research Publication

D. Kumar J, .N, H., .S, K., .N, M., S, S., .L, V., and Nag, P. V. Sunil, “Wavelet based Fault Detection for Wind Turbine”, IJCA Proceedings on International Symposium on Devices MEMS, Intelligent Systems & Communication (ISDMISC), pp. 7-10, 2011.