Fault Size Estimation Using Vibration Signatures in a Wind Turbine Test-rig

Fault size evaluation has become more significant in recent years to determine the fault size or the severity of fault apart from the fault detection for prediction of remaining useful life. The present investigation focuses on the fault size estimation of gear root crack in a wind turbine test rig using vibration signatures. A wind turbine test rig was developed at BITS-Pilani, Hyderabad Campus to simulate the working of a wind turbine. Time domain vibration signals are acquired using accelerometers for the healthy as well as faulty components. Discrete Wavelet Transform of vibration signature is performed and features are extracted from the statistical analysis of wavelet coefficients and the extracted features are used as inputs in an ANN (Artificial Neural Network) to effectively predict the size of gear root crack.