Current covariance analysis-based open-circuit fault diagnosis for voltage-source-inverter-fed vector-controlled induction motor drives

Yang, Heng; Zhou, Yang; Zhao, Jin

doi:10.1007/s43236-020-00043-5

Cited by 11 publications

(5 citation statements)

References 28 publications

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“…Yang et al [20] used the covariance of three-phase current to diagnose and locate transistor opencircuit faults by analyzing the correlation between them. Naseri et al [21] employed three Kalman filters to estimate the three-phase motor currents, and used averaged normalized residual signals as diagnostic criteria for the detection of open-switch faults.…”

Section: Motor Fault Diagnosis Methods Based On Current Signal 221 Di...mentioning

confidence: 99%

A Novel Motor Fault Diagnosis Method Based on Generative Adversarial Learning with Distribution Fusion of Discrete Working Conditions

Lan¹,

Chen²,

Yao³

2023

Computer Modeling in Engineering &Amp; Sciences

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Many kinds of electrical equipment are used in civil and building engineering. The motor is one of the main power components of this electrical equipment, which can provide stable power output. During the long-term use of motors, various motor faults may occur, which affects the normal use of electrical equipment and even causes accidents. It is significant to apply fault diagnosis for the motors at the construction site. Aiming at the problem that signal data of faulty motor lack diversity, this research designs a multi-layer perceptron Wasserstein generative adversarial network, which is used to enhance training data through distribution fusion. A discrete wavelet decomposition algorithm is employed to extract the low-frequency wavelet coefficients from the original motor current signals. These are used to train the multi-layer perceptron Wasserstein generative adversarial model. Then, the trained model is applied to generate fake current wavelet coefficients with the fused distribution. A motor fault classification model consisting of a feature extractor and pattern recognizer is built based on perceptron. The data augmentation experiment shows that the fake dataset has a larger distribution than the real dataset. The classification model trained on a real dataset, fake dataset and combined dataset achieves 21.5%, 87.2%, and 90.1% prediction accuracy on the unseen real data, respectively. The results indicate that the proposed data augmentation method can effectively generate fake data with the fused distribution. The motor fault classification model trained on a fake dataset has better generalization performance than that trained on a real dataset.

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Section: Motor Fault Diagnosis Methods Based On Current Signal 221 Di...mentioning

confidence: 99%

A Novel Motor Fault Diagnosis Method Based on Generative Adversarial Learning with Distribution Fusion of Discrete Working Conditions

Lan¹,

Chen²,

Yao³

2023

Computer Modeling in Engineering &Amp; Sciences

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“…A fault is defined as a state of deviation from the standard and usual conditions. Among the power electronic components, power semiconductors are regarded as some of the weakest and most fragile parts [25] (Figure 1). For this reason, fruitful research had been conducted on switch fault diagnosis and post-fault control methods during the past few decades.…”

Section: Introductionmentioning

confidence: 99%

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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“…where S is the covariance matrix of time series samples. In [30], the current and topological symmetry of the inverter were analyzed, and the normalized covariance between time series was selected to measure the symmetry of phase currents. This method has a high robustness and no misdiagnoses under various working conditions.…”

mentioning

confidence: 99%

“…A comparison is given in Table 1 for [15,21,26,27,30], all of which have the same research objectives. It can be seen that the distance-based methods have the advantage of high robustness and low computational cost.…”

mentioning

confidence: 99%

“…But in summary, the researches on using these distances to measure the symmetry for fault diagnosis are few, which may be a feasible research point. T medium high 9 CD + ED [26] T/4 low high 21 MhtD [15] T low high 9 Normalized covariance [30] T/2 low high 9 1 The time from the occurrence of the fault to it is located, measured in current cycles T. 2 The independence to transient disturbance such as load fluctuation. 3 The OC fault types that the method can diagnose.…”

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confidence: 99%

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A Review of Symmetry-Based Open-Circuit Fault Diagnostic Methods for Power Converters

Zhou,

Zhao,

2024

Symmetry

Self Cite

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Power converters can convert the electrical energy output by power source into specific forms required by target device. They are widely used in various fields such as electrification, transportation, and power systems, and are the core components of the systems. Power converters are composed of power semiconductor devices (such as IGBTs), which are prone to failure due to abnormal conditions and aging degradation, leading to power converter faults. Therefore, over the past twenty years, extensive fault diagnosis methods for power converters have been studied and proposed. Among them, symmetry-based methods have the characteristics of rapid diagnosis speed and strong robustness, but so far there’s no systemic summary of such methods. Therefore, this paper reviews the relevant research on fault diagnosis of power converters based on symmetry in recent years, analyzes the mathematical principles of these methods, and compares their diagnostic performance. In addition, two factors that may have an influence on the symmetry are pointed out. This paper provides references and suggestions for the future development and research of power converter fault diagnosis.

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Current covariance analysis-based open-circuit fault diagnosis for voltage-source-inverter-fed vector-controlled induction motor drives

Cited by 11 publications

References 28 publications

A Novel Motor Fault Diagnosis Method Based on Generative Adversarial Learning with Distribution Fusion of Discrete Working Conditions

A Novel Motor Fault Diagnosis Method Based on Generative Adversarial Learning with Distribution Fusion of Discrete Working Conditions

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

A Review of Symmetry-Based Open-Circuit Fault Diagnostic Methods for Power Converters

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