Fault Diagnosis Method for Switched Reluctance Machine Drive Systems Using a Switching Signal

Shin, Hye Ung; Lee, Kyo‐Beum

doi:10.1007/s42835-018-00063-z

Cited by 2 publications

(2 citation statements)

References 25 publications

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Section: Introductionmentioning

confidence: 99%

“…For this reason, fruitful research had been conducted on switch fault diagnosis and post-fault control methods during the past few decades. However, the previous studies focused on switch faults of machine drives or threephase (3-P) two-level rectifier systems [26][27][28]. In power semiconductors, the power loss appears as a thermal effect, such as a junction temperature change or thermomechanical stress accumulation [21,29].…”

Section: Introductionmentioning

confidence: 99%

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Switch Open-Fault Detection for a Three-Phase Hybrid Active Neutral-Point-Clamped Rectifier

Kim

Park

et al. 2020

Electronics

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This paper proposes a fault-detection method for open-switch failures in hybrid active neutral-point-clamped (HANPC) rectifiers. The basic HANPC topology comprises two SiC-based metal-oxide-semiconductor field-effect transistors (MOSFETs) and four Si insulated-gate bipolar transistors (IGBTs). A three-phase rectifier system using the HANPC topology can produce higher efficiency and lower current harmonics. An open-switch fault in a HANPC rectifier can be a MOSFET or IGBT fault. In this work, faulty cases of six different switches are analyzed based on the current distortion in the stationary reference frame. Open faults in MOSFET switches cause immediate and remarkable current distortions, whereas, open faults in IGBT switches are difficult to detect using conventional methods. To detect an IGBT fault, the proposed detection method utilizes some of the reactive power in a certain period to make an important difference, using the direct-quadrant (dq)-axis current information derived from the three-phase current. Thus, the proposed detection method is based on three-phase current measurements and does not use additional hardware. By analyzing the individual characteristics of each switch failure, the failed switch can be located exactly. The effectiveness and feasibility of the proposed fault-detection method are verified through PSIM simulations and experimental results.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Switch Open-Fault Detection for a Three-Phase Hybrid Active Neutral-Point-Clamped Rectifier

Kim

Park

et al. 2020

Electronics

Self Cite

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Deep Learning Algorithm for Optimized Sensor Data Fusion in Fault Diagnosis and Tolerance

Elhoseny,

Rao,

Veerasamy

et al. 2024

Int J Comput Intell Syst

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Environmental perception is one of the key technologies to realize autonomous vehicles. The fault diagnosis process involves identifying the fault that occurred or the cause of the out-of-control condition. Here, the major objective is to locate problems in detection by analysing previous data or sequential patterns of data that cause failure. This study evaluates the use of deep learning for improved sensor data fusion in fault identification and tolerance using the KITTI dataset. The input video from the dataset has been transformed to frames through median filtering. Next, feature extraction is applied to a preprocessed image, resulting in the fusion of sensor data. Data fusion is then carried out utilizing an enhanced RPN (region proposal network). The enhanced RPN also has a loss function (object detection loss, bounding box loss and target classification loss), an estimate of ROI and feature extraction network (FEN). Through the use of the COOT connected blue monkey optimization (CCBMO) model, the weight of the optimally enhanced RPN is established. Next, using global non-maximum suppression with both global and local confidence, fault identification and tolerance are carried out. From the analysis, it clearly shows that proposed method accomplished better results in terms of accuracy, precision and specificity of 97.78%, 93.76% and 93.43%, respectively, when compared with various conventional models with respect to diverse performance measures.

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Fault Diagnosis Method for Switched Reluctance Machine Drive Systems Using a Switching Signal

Cited by 2 publications

References 25 publications

Switch Open-Fault Detection for a Three-Phase Hybrid Active Neutral-Point-Clamped Rectifier

Switch Open-Fault Detection for a Three-Phase Hybrid Active Neutral-Point-Clamped Rectifier

Deep Learning Algorithm for Optimized Sensor Data Fusion in Fault Diagnosis and Tolerance

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