Voltage and Current Sensor Fault Diagnosis Method for Traction Converter with Two Stator Current Sensors

Tao, Hongwei; Peng, Tao; Yang, Chao; Gao, Jinqiu; Yang, Chunhua; Gui, Weihua

doi:10.3390/s22062355

Cited by 10 publications

(3 citation statements)

References 27 publications

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“…To simulate this fault, a constant (known as the offset fault) is added to the output of the current Ia. This approach has been widely used in previous studies [28]- [30] to analyze the effects of offset faults in various systems. By considering this fault scenario, we can gain valuable insights into the behavior of the system and assess its robustness in the presence of such faults.…”

Section: Resultsmentioning

confidence: 99%

Real-time current sensor fault detection and localization in DFIG wind turbine systems

Touioui,

Ganouche,

Ahmida

et al. 2023

IJPEDS

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<span lang="EN-US">The degree of reliability is one of the main issues in having the uninterrupted operation of fault-tolerant measurement and control systems. This paper presents a technique for detecting and localizing current sensor fault in doubly fed induction generator wind turbine systems (DFIG-WT). For this purpose, a methodology divided into three steps has been carried out and is presented as follows: the first step is the application of the zero-sequence component as an indicator of the presence of the sensor fault. The second step is based on the application of Concordia transformation on the current signals to generate different criteria for localizing the faulty sensor. Finally, an artificial neural network model is developed to analyze the localization criteria and identify the faulty sensor. All simulations are carried out in MATLAB/Simulink environment. Results show that the proposed technique is effective and can be used in real-time fault detection and localization in the DFIG-WT.</span>

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Section: Resultsmentioning

confidence: 99%

Real-time current sensor fault detection and localization in DFIG wind turbine systems

Touioui,

Ganouche,

Ahmida

et al. 2023

IJPEDS

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“…The accuracy of the feedback signals collected and provided by sensors deeply influences the control unit of the system [8]. Due to the complex operating conditions, such as humidity, temperature, and static electrical corrosion, unexpected failures may occur in sensors [9], which may lead to signals' deviation provided by sensors and even the catastrophic subsequent failure of high-speed trains [10,11]. Therefore, methods that are capable of detecting and diagnosing different sensor faults have application value and are of great significance for rectifiers.…”

Section: Introductionmentioning

confidence: 99%

Voltage and Current Sensor Fault Diagnosis Method for Traction Rectifier in High-Speed Trains

Yu,

Song,

Tao

et al. 2024

Electronics

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The traction rectifier plays a key role in high-speed trains. Unexpected failure often occurs in the sensors of the rectifier, which may affect the control performance of the electric traction rectifier and even cause serious deterioration to high-speed trains. A sensor fault diagnosis method is presented in this paper, considering three kinds of common fault types. It can not only locate the sensor fault, but also identify fault types. Based on the influences of the sensor faults, the fault diagnosis thresholds can be calculated quantitatively. No additional hardware is required. First, the model of the rectifier is established, and the estimator is built. The current residuals with different faults can be obtained. Next, residuals are analyzed and features are acquired. Then, diagnosis functions are constructed, which are used for fault location and fault type identification. Finally, the feasibility and effectiveness of the method have been confirmed by the experimental results.

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“…Many fault diagnosis methods have been investigated for HST systems in recent years. Among these, fault diagnosis methods have been investigated for traction devices of HSTs, such as rectifier (Chen et al, 2021), converter (Tao et al, 2022), traction motor (Zou et al, 2021) and pantograph (Lu et al, 2021). Other excellent results have been reported for brake system (Ji, 2021), bogie (Huang et al, 2021) and suspension system (Zhang et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Optimized adaptive filtering for fault estimation of the dynamics of high-speed train based on robust extended Kalman filter

Liang

Wang

et al. 2023

Transactions of the Institute of Measurement and Control

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In this paper, an optimized adaptive robust extended Kalman filter is proposed based on random weighting factors and an improved whale optimization algorithm for fault estimation of the dynamics of high-speed trains with constant time delays, drastically changing noise and stochastic uncertainties. Robust upper bounds are proposed to improve the performance of the extended Kalman filter by decreasing the influence of the linearization error on filtering for the dynamics of high-speed trains with constant time delays, and its robustness is proven to guarantee the feasibility of the proposed upper bounds. Furthermore, considering drastically changing noise with unknown statistics, a random weighting adaptive algorithm is proposed to implement unbiased noise estimation so that the robust extended Kalman filter can still be implemented well. In addition, a differential evolution algorithm and adaptive parameter are introduced to improve the performance of the whale optimization algorithm so that the stochastic uncertainties are optimized, and the influence of the stochastic uncertainties on filtering is further decreased. The simulation results in the three conditions show that, compared with the variational Bayes adaptive iterated extended Kalman filter, using the proposed method, the position, speed and fault estimation errors are decreased by 31.8%, 33.2% and 28.3%, respectively, on average, which depends on more accurate noise estimation.

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Voltage and Current Sensor Fault Diagnosis Method for Traction Converter with Two Stator Current Sensors

Cited by 10 publications

References 27 publications

Real-time current sensor fault detection and localization in DFIG wind turbine systems

Real-time current sensor fault detection and localization in DFIG wind turbine systems

Voltage and Current Sensor Fault Diagnosis Method for Traction Rectifier in High-Speed Trains

Optimized adaptive filtering for fault estimation of the dynamics of high-speed train based on robust extended Kalman filter

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