Analysis and Modeling of Three Winding Stator Interturn Fault on Induction Machine for Electric Vehicle Application

Praneeth, A. V. J. S.; Anand, N. Vijaya; Sandhu, K. S.; Williamson, Sheldon S.

doi:10.1109/pedes.2018.8707867

Cited by 3 publications

(2 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As one of the most common faults in PMSM, the stator winding inter-turn short circuit (ITSC) fault is usually hard to identify [3]. Moreover, without timely and appropriate management, the PMSM runs into a severe short circuit fault or even an open circuit fault [4].…”

Section: Introductionmentioning

confidence: 99%

Multiscale Kernel-Based Residual CNN for Estimation of Inter-Turn Short Circuit Fault in PMSM

Song

Wang

Lai

et al. 2022

Sensors

View full text Add to dashboard Cite

The diagnosis of an inter-turn short circuit (ITSC) fault at its early stage is very important in permanent magnet synchronous motors as these faults can lead to disastrous results. In this paper, a multiscale kernel-based residual convolutional neural network (CNN) algorithm is proposed for the diagnosis of ITSC faults. The contributions are majorly located on two sides. Firstly, a residual learning connection is embedded into a dilated CNN to overcome the defects of the conventional convolution and the degradation problem of a deep network. Secondly, a multiscale kernel algorithm is added to a residual dilated CNN architecture to extract high-dimension features from the collected current signals under complex operating conditions and electromagnetic interference. A motor fault experiment with both constant operating conditions and dynamics was conducted by setting the fault severity of the ITSC fault to 17 levels. Comparison with five other algorithms demonstrated the effectiveness of the proposed algorithm.

show abstract

Section: Introductionmentioning

confidence: 99%

Multiscale Kernel-Based Residual CNN for Estimation of Inter-Turn Short Circuit Fault in PMSM

Song

Wang

Lai

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…A faulty IM model was established based on multiloop theory and the currents were analyzed to detect the BRB fault in [12]. For stator fault, a model with interturn short-circuit fault was established based on reference frame transformation theory and the fault detection was realized by analyzing the changes of currents, speed, and torque in [13,14]. e influence of the harmonics of the supply voltage was considered to establish a dynamic model with interturn short-circuit fault and the instantaneous power of the motor was used to detect the stator fault in [15].…”

Section: Introductionmentioning

confidence: 99%

Method for Identifying Stator and Rotor Faults of Induction Motors Based on Machine Vision

Lipeng

Xiang

Wang

et al. 2021

Mathematical Problems in Engineering

View full text Add to dashboard Cite

The detection results need to be analyzed and distinguished by professional technicians in the fault detection methods for induction motors based on signal processing and it is difficult to realize the automatic identification of stator and rotor faults. A method for identifying stator and rotor faults of induction motors based on machine vision is proposed to solve this problem. Firstly, Park’s vector approach (PVA) is used to analyze the three-phase currents of the motor to obtain Park’s vector ring (PVR). Then, the local binary patterns (LBP) and gray level cooccurrence matrix (GLCM) are combined to extract the image features of PVR. Finally, the vectors of image features are used as input and the types of induction motor faults are identified with the help of a random forest (RF) classifier. The proposed method has achieved high identification accuracy in both the Maxwell simulation experiment and the actual motor experiment, which are 100% and 95.83%, respectively.

show abstract

Implementation of an On-line Diagnosis Algorithm of PMSM Inter-turn Short Circuit Based on Search Coil and FPGA

Cheng

Sun

et al. 2022

2022 IEEE 5th International Electrical and Energy Conference (CIEEC)

View full text Add to dashboard Cite

Analysis and Modeling of Three Winding Stator Interturn Fault on Induction Machine for Electric Vehicle Application

Cited by 3 publications

References 19 publications

Multiscale Kernel-Based Residual CNN for Estimation of Inter-Turn Short Circuit Fault in PMSM

Multiscale Kernel-Based Residual CNN for Estimation of Inter-Turn Short Circuit Fault in PMSM

Method for Identifying Stator and Rotor Faults of Induction Motors Based on Machine Vision

Implementation of an On-line Diagnosis Algorithm of PMSM Inter-turn Short Circuit Based on Search Coil and FPGA

Contact Info

Product

Resources

About