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Fault diagnosis of drive train gearboxes is a prominent challenge in wind turbine condition monitoring. Many machine learning algorithms have been applied to gearbox fault diagnosis. However, many of the current machine learning algorithms did not provide satisfactory fault diagnostic results due to their shallow architectures. Recently, a class of machine learning models with deep architectures called...
This paper proposes a new fault detection and identification framework for drivetrain gearboxes of wind turbines equipped with doubly-fed induction generators (DFIGs) based on the fusion of DFIG stator and rotor current signals. First, the characteristic frequencies of gearbox faults in DFIG stator and rotor currents are analyzed. Different time- and frequency-domain features of gearbox faults in...
This paper proposes a new fault detection and identification framework for drivetrain gearboxes of wind turbines equipped with doubly-fed induction generators (DFIGs) based on the fusion of DFIG stator and rotor current signals. First, the characteristic frequencies of gearbox faults in DFIG stator and rotor currents are analyzed. Different time- and frequency-domain features of gearbox faults in...
Gearbox faults are a leading reliability issue in wind turbines. Generator current-based methods have been successfully used in gearbox fault diagnosis and have shown advantages over the traditional vibration-based techniques in terms of implementation, cost, and reliability. This paper proposed a new generator stator current-based fault diagnostic method for the gearboxes in doubly-fed induction...
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