Multiple Open-Circuit Fault Diagnosis Method in NPC Rectifiers Using Fault Injection Strategy

Chen, Mingyun; He, Yigang

doi:10.1109/tpel.2022.3150885

Cited by 21 publications

(3 citation statements)

References 39 publications

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“…Wang et al [3] combined an improved Dempster-Shafer (DS) evidence theory with a backpropagation (BP) neural network to enhance the accuracy of diagnosing open-circuit faults in inverter transistors. Mingyun Chen et al [4] developed a fault injection strategy to aid in differentiating between internal and external switch faults within 3L-NPC rectifiers. Their method facilitates the quick and accurate detection of both single and multiple switch faults, improving overall system reliability.…”

Section: Introductionmentioning

confidence: 99%

A Method of Diagnosing Analog Circuit Soft Faults Using Boruta Features and LightGBM

Chen,

Hu,

Han

et al. 2024

Electronics

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Modern electronic power systems rely heavily on analog circuits. The accurate detection of analog circuit faults, especially soft faults, is of great significance for the maintenance and inspection of electronic systems. This paper proposes the application of the Boruta feature selection method to the field of the soft fault diagnosis of analog circuits to screen out low-dimensional and efficient feature components from the high-dimensional time-domain statistical features and frequency-domain features of circuit responses. Then, the feature components are used as the input to train the LightGBM classification model, and the Bayesian optimization method is introduced to optimize the model’s hyperparameters. Finally, the trained fault diagnosis model is verified in two typical experimental circuits, and satisfactory accuracy is obtained.

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Section: Introductionmentioning

confidence: 99%

A Method of Diagnosing Analog Circuit Soft Faults Using Boruta Features and LightGBM

Chen,

Hu,

Han

et al. 2024

Electronics

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“…Consequently, multilevel converters, especially the neutral-point diode-clamped converter (NPC), become a viable solution [26]. Typically, multilevel converters are used in medium-voltage high-power applications [27]. They have the advantage of higher voltage ratings with lower device stresses with the inherited lower harmonics [28].…”

Section: Introductionmentioning

confidence: 99%

Two-Leg Neutral-Point Diode-Clamped Active Front-End Rectifier

Abdel-Aziz,

Elgenedy,

Williams

2024

IEEE J. Emerg. Sel. Topics Power Electron.

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Active front-end boost rectifiers can replace the uncontrolled diode bridge rectifiers for ac-dc conversion offering high power quality with near unity power factor. The four-switch, B4, topology is gaining interest, either as an inverter or a rectifier, where each switch should withstand the full dc link voltage. Higher voltage-rated power semiconductor devices not only imply slower response with lower overall efficiency but also higher cost and size. Thus, multilevel inverters become a viable solution. This paper investigates a two-leg neutral-point diode-clamped B8 rectifier allowing the series connection of fast, efficient, and low voltage rating switches. The proposed rectifier has better performance and efficiency than the B4 rectifier. Only two inductors instead of three are required. Model predictive current control (MPCC) is developed for accurate current tracking. A model of the proposed rectifier is detailed for the implementation of MPCC. The concept is validated by simulation and experimentation.

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“…Wang et al [3] proposed to use an im-proved DS (Dempster-Shafer, abbreviated as DS) evidence theory and BP neural network to improve the accuracy of fault diagnosis of open circuit faults in three-phase voltage source inverter transistors. Mingyun Chen et al [4] designed a fault injection strategy to make it easier to distinguish between internal switch faults and external switch faults, so as to more accurately and quickly detect single switch faults and multiple switch faults in 3L-NPC rectifiers. Tiancheng Shi [5] proposed an improved diagnostic method based on deep belief network (DBN) and least squares support vector machine (LSSVM), which realized the diagnosis of various switch faults in pulse-width modulation voltage source rectifier systems, and has good anti-interference and diagnostic speed.…”

Section: Introductionmentioning

confidence: 99%

An analog circuit soft fault diagnosis method based on Boruta feature selection and LightGBM model

Chen,

Hu,

Han

et al. 2024

Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024)

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Analog circuits are an important part of modern electronic power systems. Accurate detection of analog circuit faults, especially soft faults, is of great significance for the maintenance and inspection of electronic systems. This paper proposes to apply the Boruta feature selection method to the field of soft fault diagnosis of analog circuits to screen out lowdimensional and efficient feature components from the high-dimensional time-domain statistical features and frequencydomain features of circuit responses. Then, the feature components are used as input to train the LightGBM classification model, and the Bayesian optimization method is introduced to optimize the model hyperparameters. Finally, the trained fault diagnosis model is verified in two typical experimental circuits, and satisfactory accuracy is obtained.

show abstract

Multiple Open-Circuit Fault Diagnosis Method in NPC Rectifiers Using Fault Injection Strategy

Cited by 21 publications

References 39 publications

A Method of Diagnosing Analog Circuit Soft Faults Using Boruta Features and LightGBM

A Method of Diagnosing Analog Circuit Soft Faults Using Boruta Features and LightGBM

Two-Leg Neutral-Point Diode-Clamped Active Front-End Rectifier

An analog circuit soft fault diagnosis method based on Boruta feature selection and LightGBM model

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