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Full-Text Articles in Engineering
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 …
Frequency Demodulation-Aided Condition Monitoring For Drivetrain Gearboxes, Dingguo Lu, Wei Qiao
Frequency Demodulation-Aided Condition Monitoring For Drivetrain Gearboxes, Dingguo Lu, Wei Qiao
Department of Electrical and Computer Engineering: Faculty Publications
Condition monitoring and fault diagnosis (CMFD) of drivetrain gearboxes has become a prominent challenge in assorted industries. Current-based diagnostic techniques have significant advantages over traditional vibration-based techniques in terms of accessibility, cost, implementation and reliability. This paper proposes a current-based, frequency demodulation-aided CMFD method for drivetrain gearboxes. A mathematical model is developed for a drivetrain consisting of a two-stage gearbox and a permanent magnet synchronous generator (PMSG), from which the characteristic frequencies of gearbox faults in the PMSG stator current are derived. An adaptive signal resampling method is proposed to convert the variable fault characteristic frequencies to constant values for …
Adaptive Feature Extraction And Svm Classification For Real-Time Fault Diagnosis Of Drivetrain Gearboxes, Dingguo Lu, Wei Qiao
Adaptive Feature Extraction And Svm Classification For Real-Time Fault Diagnosis Of Drivetrain Gearboxes, Dingguo Lu, Wei Qiao
Department of Electrical and Computer Engineering: Faculty Publications
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 generation algorithm are integrated in the proposed method for effective extraction of the features of gearbox faults from the stator current signal of the AC electric machine connected to the gearbox. A radial basis function kernel-SVM classifier is designed to identify the fault in the gearbox according to …
Current-Based Diagnosis For Gear Tooth Breaks In Wind Turbine Gearboxes, Dingguo Lu, Xiang Gong, Wei Qiao
Current-Based Diagnosis For Gear Tooth Breaks In Wind Turbine Gearboxes, Dingguo Lu, Xiang Gong, Wei Qiao
Department of Electrical and Computer Engineering: Faculty Publications
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 twostage gearbox and a permanent magnet (PM) generator, from which the characteristic frequencies of gear tooth breaks in generator stator current frequency spectra are clearly identified. A adaptive signal resampling algorithm is proposed to convert the variable fault characteristic frequencies to constant values for WTs running at variable speeds. A fault detector is …