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Full-Text Articles in Computer Engineering
A Survey On Wind Turbine Condition Monitoring And Fault Diagnosis−Part I: Components And Subsystems, Deli Qiao, Dingguo Lu
A Survey On Wind Turbine Condition Monitoring And Fault Diagnosis−Part I: Components And Subsystems, Deli Qiao, Dingguo Lu
Department of Electrical and Computer Engineering: Faculty Publications
This paper provides a comprehensive survey on the state-of-the-art condition monitoring and fault diagnostic technologies for wind turbines. The Part I of this survey briefly reviews the existing literature surveys on the subject, discusses the common failure modes in the major wind turbine components and subsystems, briefly reviews the condition monitoring and fault diagnostic techniques for these components and subsystems, and specifically discusses the issues of condition monitoring and fault diagnosis for offshore wind turbines.
A Survey On Wind Turbine Condition Monitoring And Fault Diagnosis−Part Ii: Signals And Signal Processing Methods, Wei Qiao, Dingguo Lu
A Survey On Wind Turbine Condition Monitoring And Fault Diagnosis−Part Ii: Signals And Signal Processing Methods, Wei Qiao, Dingguo Lu
Department of Electrical and Computer Engineering: Faculty Publications
This paper provides a comprehensive survey on the state-of-the-art condition monitoring and fault diagnostic technologies for wind turbines. The Part II of this survey focuses on the signals and signal processing methods used for wind turbine condition monitoring and fault diagnosis.
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. …
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 …
Current-Based Fault Detection For Wind Turbine Systems Via Hilbert-Huang Transform, Dingguo Lu, Wei Qiao, Xiang Gong, Liyan Qu
Current-Based Fault Detection For Wind Turbine Systems Via Hilbert-Huang Transform, Dingguo Lu, Wei Qiao, Xiang Gong, Liyan Qu
Department of Electrical and Computer Engineering: Faculty Publications
Mechanical failures of wind turbines represent a significant cost in both repairs and downtime. Detecting incipient faults of wind turbine components permits maintenance to be scheduled and failed parts to be repaired or replaced before causing failures of other components or catastrophic failure of the system. This paper proposes a Hilbert-Huang transform (HHT)-based algorithm to effectively extract fault signatures in generator current signals for wind turbine fault diagnosis by using the HHT’s capability of accurately representing the instantaneous amplitude and frequency of nonlinear and nonstationary signals. A phase-lock-loop (PLL) method is integrated to estimate wind turbine rotating speed, which is …
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 …