Concurrent fault diagnosis of modular multilevel converter with Kalman filter and optimized support vector machine

Zhang, Yong; Hu, Huanzhen; Liu, Zhenxing; Zhao, Min; Cheng, Lin

doi:10.1080/21642583.2019.1650840

Cited by 17 publications

(6 citation statements)

References 22 publications

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“…In 49 the authors implement an open circuit fault detection method to prevent the whole system from shutdowns based on the Kalman filter and optimized SVM. The fault is detected using KF and located fault by using optimized SVM.…”

Section: Fault Diagnosis and Control Techniques For MMCmentioning

confidence: 99%

A comprehensive review of fault diagnosis and fault-tolerant control techniques for modular multi-level converters

et al. 2022

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Background Many faults occur in the modular multi-level converters (MMCs), including unbalancing capacitor voltage, lower and upper arm unbalancing, the line to line voltage unbalancing, sensors and actuators fault, system fault, and sub-modules fault in high as well as medium voltage applications. Introduction Several fault-tolerant approaches are presented to overcome these problems, such as active fault-tolerant control system (AFTCS), passive fault-tolerant control system (PFTCS), hybrid fault-tolerant control system (HFTCS), redundant system technique, special power circuit with the controller, and zero sequence voltage methods, which we will explain extensively in this article. Methodology This review emphasizes the types of faults in the MMCs and discusses the protection methods under failure conditions. The MMC is more popular in high voltage applications because it not only improves the quality of the grid but also has good harmonic performance in high power transmission. There is no need for any isolated dc sources to operate it. When faults are removed, the efficiency and reliability of the system will be increased. Results This extensive explanation of the current literature on MMC fault diagnosis and control techniques will conclude which methods provide a more valuable solution. Finally, this paper discusses the best approach to reduce MMC faults and provides a future research direction to the readers.

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Section: Fault Diagnosis and Control Techniques For MMCmentioning

confidence: 99%

A comprehensive review of fault diagnosis and fault-tolerant control techniques for modular multi-level converters

et al. 2022

View full text Add to dashboard Cite

show abstract

“…There are many fault detection approaches for multi-level converters, including comparison between measured and reference values, the sliding mode observer [14], Lyapunov theory [15], the Kalman filter algorithm [16,17], Fourier transform [18], Park transformation [19], wavelet transform [20], machine learning [21], neural network approaches [22], and the Filippov method [23].…”

Section: Introductionmentioning

confidence: 99%

Open-Circuit Fault Detection and Location in AC-DC-AC Converters Based on Entropy Analysis

Morel

Akrad

2023

Energies

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Inverters and converters contain more and more power electronics switches which may subsequently affect their reliability. Therefore, fault detection and location are essential to improve their reliability and to ensure continuous operation. In this paper, an AC−DC−AC converter with three-phase inverter is investigated under permanent, single and multiple open-circuit fault scenarios. Many entropies and multiscale entropies are then proposed to evaluate the complexity of the output currents by quantifying their entropies over a range of temporal scales. Among the multitude of entropies, only some entropies are able to differentiate healthy from open-circuit faulty conditions. Moreover, the simulation results show that these entropies are able to detect and locate the arms of the bridge with open-circuit faults.

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“…Software-based methods can further be categorized into model-based methods and signal processing-based methods [ 9 , 10 ], according to whether the monitoring characteristics are inner characteristics or output characteristics [ 11 ]. The observers such as Luenberger observer [ 12 ], sliding mode observer [ 13 , 14 ], and Kalman filter observer [ 15 , 16 ], are prevalent model-based methods used to provide the detection references. Signal processing-based methods have been considered reliable and effective by several researchers [ 17 , 18 , 19 , 20 ] in recent years.…”

Section: Introductionmentioning

confidence: 99%

Open-Circuit Fault Detection and Classification of Modular Multilevel Converters in High Voltage Direct Current Systems (MMC-HVDC) with Long Short-Term Memory (LSTM) Method

Wang

Ahmed

et al. 2021

Sensors

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Fault detection and classification are two of the challenging tasks in Modular Multilevel Converters in High Voltage Direct Current (MMC-HVDC) systems. To directly classify the raw sensor data without certain feature extraction and classifier design, a long short-term memory (LSTM) neural network is proposed and used for seven states of the MMC-HVDC transmission power system simulated by Power Systems Computer Aided Design/Electromagnetic Transients including DC (PSCAD/EMTDC). It is observed that the LSTM method can detect faults with 100% accuracy and classify different faults as well as provide promising fault classification performance. Compared with a bidirectional LSTM (BiLSTM), the LSTM can get similar classification accuracy, requiring less training time and testing time. Compared with Convolutional Neural Networks (CNN) and AutoEncoder-based deep neural networks (AE-based DNN), the LSTM method can get better classification accuracy around the middle of the testing data proportion, but it needs more training time.

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Concurrent fault diagnosis of modular multilevel converter with Kalman filter and optimized support vector machine

Cited by 17 publications

References 22 publications

A comprehensive review of fault diagnosis and fault-tolerant control techniques for modular multi-level converters

A comprehensive review of fault diagnosis and fault-tolerant control techniques for modular multi-level converters

Open-Circuit Fault Detection and Location in AC-DC-AC Converters Based on Entropy Analysis

Open-Circuit Fault Detection and Classification of Modular Multilevel Converters in High Voltage Direct Current Systems (MMC-HVDC) with Long Short-Term Memory (LSTM) Method

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