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This paper presents a genetic algorithm (GA)-support vector machine (SVM) hybrid classifier for multiclass fault identification of drivetrain gearboxes in variable-speed operational conditions. An adaptive feature extraction algorithm is employed to effectively extract the features of gearbox faults from the stator current signal of an AC machine connected to the gearbox. The multiclass GA-SVM classifier...
Drivetrain gearboxes play an important role in many modern industrial applications. This paper presents a novel method consisting of adaptive feature extraction and support vector machine (SVM)-based classification for condition monitoring and fault diagnosis of drivetrain gearboxes operating in variable-speed conditions. An adaptive signal resampling algorithm, a frequency tracker, and a feature...
Gearbox faults constitute a significant portion of all faults and downtime in wind turbines (WTs). Current-based gearbox fault diagnosis has significant advantages over traditional vibration-based techniques in terms of cost, implementation, and reliability. This paper derives a mathematical model for a WT drive train consisting of a two-stage gearbox and a permanent magnet (PM) generator, from which...
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