Wavelet Based Fault Detection for Wind Turbin

Wavelet Based Fault Detection for Wind Turbin

Wavelet based Fault Detection for Wind Turbine

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 t...

Variable Speed Wind Turbine DFIG Back to Back Converters Open-Circuit Fault Diagnosis by Using of Combiniation Signal-Based and Model-Based Methodes

Condition monitoring (CM) and Fault Detection (FD) of wind turbine lead to increase in reliability and availability of turbine. IGBT open circuit of wind turbine converter will bring about depletion in output current of converter and as a result, reduction in production of wind turbine power. In this research, back to back converter IGBT open - gate fault for wind turbine based on DFIG is detec...

Robust Model- Based Fault Detection and Isolation for V47/660kW Wind Turbine

In this paper, in order to increase the efficiency, to reduce the cost and to prevent the failures of wind turbines, which lead to an extensive break down, a robust fault diagnosis system is proposed for V47/660kW wind turbine operated in Manjil wind farm, Gilan province, Iran. According to the acquired data from Iran wind turbine industry, common faults of the wind turbine such as sensor fault...

AN INTELLIGENT FAULT DIAGNOSIS APPROACH FOR GEARS AND BEARINGS BASED ON WAVELET TRANSFORM AS A PREPROCESSOR AND ARTIFICIAL NEURAL NETWORKS

In this paper, a fault diagnosis system based on discrete wavelet transform (DWT) and artificial neural networks (ANNs) is designed to diagnose different types of fault in gears and bearings. DWT is an advanced signal-processing technique for fault detection and identification. Five features of wavelet transform RMS, crest factor, kurtosis, standard deviation and skewness of discrete wavelet co...