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Electrical and Computer Engineering
Department of Electrical and Computer Engineering: Faculty Publications
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A Ga-Svm Hybrid Classifier For Multiclass Fault Identification Of Drivetrain Gearboxes, Dingguo Lu, Wei Qiao
A Ga-Svm Hybrid Classifier For Multiclass Fault Identification Of Drivetrain Gearboxes, Dingguo Lu, Wei Qiao
Department of Electrical and Computer Engineering: Faculty Publications
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 is used to identify the faults in the gearbox according to the fault features extracted. A GA is designed to find the optimal parameters of the SVM to obtain the best classification accuracy. The proposed hybrid classifier is validated on a gearbox connected with …
Fault Diagnosis For Drivetrain Gearboxes Using Pso-Optimized Multiclass Svm Classifier, Dingguo Lu, Wei Qiao
Fault Diagnosis For Drivetrain Gearboxes Using Pso-Optimized Multiclass Svm Classifier, Dingguo Lu, Wei Qiao
Department of Electrical and Computer Engineering: Faculty Publications
A novel method consisting of an adaptive feature extraction scheme and a particle swarm optimization (PSO)- optimized multiclass support vector machine (SVM) classifier is proposed for condition monitoring and fault diagnosis of drivetrain gearboxes in variable-speed operational conditions. The adaptive feature extraction scheme consists of an adaptive signal resampling algorithm, a frequency tracker, and a feature generation algorithm for effective extraction of the features of gearbox faults from the stator current signal of the AC electric machine connected to the gearbox. The multiclass SVM classifier is designed to identify different faults in the gearbox according to the fault features extracted. …