An Efficient Method of Fault Detection and Classification for Wind Power Generator

Ming-Shou An, Gi-Woo Kim, Dae-Seong Kang
2015 unpublished
In recently, wind power generation has become an effective renewable energy technology. But failure of wind turbine has been frequently and more serious, and need more costs of operation and maintenance on account of continuing to achieve large-scale. To solve this problem, it is necessary to research and develop the remote monitoring system. It consists of data acquisition, data analysis and fault diagnosis. For data acquisition, there are various sensors employed to collect the signal from
more » ... the signal from wind turbines. Wireless Sensor Network (WSN) to collect and transmit data on the status of individual parts in real-time and they diagnose faults through a signal analysis system. To extract feature information of the classified fault and normal signals pattern, wavelet analysis and neural network were applied.
doi:10.14257/astl.2015.98.33 fatcat:sxjg4olew5dmhbw53pj5kis6tq