Article
Energy & Fuels
Guohua Li, Liangjun Wang, Feng Li
Summary: A hysteresis space vector pulse width modulation (SVPWM) reconfigurable fault-tolerant method for single-phase voltage source multi-level inverter with current tracking is proposed. The method analyzes the influence of single switch open circuit fault and double switches open circuit fault, and obtains the equivalent replacement of the voltage vector based on the topology reconstruction. It can accurately track the reference current.
Article
Engineering, Electrical & Electronic
Moises J. B. B. Davi, Mario Oleskovicz, Felipe Lopes
Summary: This paper investigates the impact of Inverter-Based Resources (IBRs) on fault diagnosis systems in power systems. It addresses the lack of evaluation and solutions for impedance-based fault location in lines connecting IBRs to the grid. The proposed multi-method methodology minimizes the fault location errors and shows promising results in the simulations conducted using PSCAD software.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Xinmin Li, Shaozhen Li, Wei Chen, Tingna Shi, Changliang Xia
Summary: The proposed method aims to diagnose open-circuit faults quickly and accurately in brushless dc motor inverters to ensure safe operation. It utilizes a topology for current path detection and a method based on current path change to identify and locate faults. The method improves fault diagnosis speed and is not affected by sudden load changes. It allows for prompt handling of faults and ensures reliable motor operation. Experimental results validate the effectiveness of this method.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Automation & Control Systems
Negar Noroozi, Mokhtar Yaghoubi, Mohammad Reza Zolghadri
Summary: This article introduces a cost-effective solution for switching short-circuit fault diagnosis in a three-phase quasi-Z-source inverter, utilizing a peripheral circuit and fault-diagnosis algorithm to identify the fault location before critical overcurrent conditions occur, preventing secondary damage in the system. A qZSI prototype has been implemented to validate the proposed method's satisfactory performance.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Engineering, Electrical & Electronic
Ali Shakeri Kahnamouei, Saeed Lotfifard
Summary: This article proposes a fault location identification method for radial power distribution systems with inverter-interfaced distributed generations (IIDGs) that can enhance the accuracy of results by utilizing multiple data types and considering uncertainties in the dataset, applicable to different load types.
IEEE TRANSACTIONS ON POWER DELIVERY
(2023)
Article
Engineering, Marine
Guangfeng Jin, Tianzhen Wang, Yassine Amirat, Zhibin Zhou, Tao Xie
Summary: This paper proposes a layering linear discriminant analysis method to address the issue of multimodal fault samples in current sensor faults. The method divides historical fault data based on sensor fault severity layer-by-layer, uses the kappa coefficient to end the training process, and employs a BP neural network to estimate fault severity.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Information Systems
Yu Luo, Li Zhang, Chunyang Chen, Kang Li, Tianjian Yu, Kaidi Li
Summary: This paper presents a method for detecting and locating single and double switch open circuit faults in three phase voltage source inverters based on current model parameter estimation. The method utilizes the measurement of inverter currents to build a dynamic model and uses a fast recursive algorithm to estimate the model parameters. A simplified K-Nearest Neighbour algorithm is employed to detect the closest distance between the monitored fault diagnosis vectors and the normal vectors. A simple and effective function is designed to locate the faulty switches based on the analysis of the identified vectors and those in the base matrix.
Article
Energy & Fuels
Yabo Cui, Rongjie Wang, Yupeng Si, Shiqi Zhang, Yichun Wang, Anhui Lin
Summary: This paper proposes an end-to-end fault diagnosis method based on Gramian Angular Summation Field and improved AlexNet network, which can diagnose fault results by collecting only the single-phase line voltage. The collected one-dimensional timing signal is mapped into two-dimensional images through the Gram summation angle field algorithm, and then feature extraction is performed by the improved AlexNet. Finally, the fault diagnosis result is output by the Softmax layer. Simulation experiments show that this method can automatically extract features helpful for fault identification from raw data, achieving a fault diagnosis rate as high as 99.72% and diagnosing both single faults and multiple faults in different phases. Compared with other methods, the proposed method has a better fault feature extraction effect and higher fault diagnosis accuracy.
Article
Engineering, Multidisciplinary
Shuzhi Gao, Yulong Ren, Yimin Zhang, Tianchi Li
Summary: This paper proposes an improved energy entropy fault diagnosis method and a location method based on vibration amplitude attenuation for diagnosing and locating bearing faults effectively. By increasing vibration amplitude, the accuracy of fault diagnosis can be improved, and taking the logarithm of the vibration signal attenuation function allows for precise location of rolling bearing outer raceway faults. Comparing experiments with other methods demonstrates the effectiveness of the proposed improvements.
Article
Engineering, Electrical & Electronic
Mahdi Emadaleslami, MohammadSadegh KhajueeZadeh, Farid Tootoonchian
Summary: This paper successfully diagnoses the location of static eccentricity in the resolver using a Siamese network with limited data, and it performs better compared to other neural networks.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Computer Science, Information Systems
Chukwuemeka N. N. Ibem, Mohamed E. E. Farrag, Ahmed A. A. Aboushady, Sherif M. M. Dabour
Summary: This study presents a novel integration of signal and data-driven fault-diagnosis approaches to detect open-circuit switch faults in three-phase inverters. The proposed technique uses the average root-mean-square (RMS) ratio of the phase current as the key extraction feature, which can estimate the fault types and faulty switches irrespective of changes in the running load. Ensemble-bagged machine learning classification is used to accurately predict the faulty switch in the inverter.
Article
Computer Science, Information Systems
Kuei-Hsiang Chao, Long-Yi Chang, Chien-Chun Hung
Summary: A fault diagnosis system for inverters based on a CMAC is proposed in this paper, and the feasibility of the system is validated through experiments and analysis.
Article
Engineering, Electrical & Electronic
Haoran Yin, Yong Chen, Zhangyong Chen, Meng Li
Summary: This paper presents an adaptive fast voltage-based real-time open-switch fault location method for voltage source inverters (VSIs). By calculating the voltage deviation for each phase, this method enables fault location without the need for additional hardware and easy integration into the system. The adaptive threshold design takes into account various error factors to improve accuracy, as demonstrated through simulations and experiments.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2021)
Article
Engineering, Electrical & Electronic
Weiwei Zhang, Yigang He
Summary: This article proposes an OC fault diagnosis method for grid-tied T-type three-level inverters, which hierarchically diagnoses the group-level and device-level faults. The method divides the switches in one phase into two groups based on the current distortion similarity analysis with various power factors operation. The group-level fault detection is implemented by locating the half-cycle where the zero-section phenomenon occurs, and the device-level fault location is realized by injecting specific switching signals. Simulations and experiments verify the correctness and robustness of the proposed approach, which can locate the OC fault within 6 ms.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2023)
Article
Acoustics
Chongyu Wang, Yonghui Xie, Di Zhang
Summary: This paper discusses the research on intelligent fault diagnosis using deep learning, focusing on the issues of neural network model design and data training. It proposes a unified neural network structure based on Resnet and improves diagnostic performance through transfer learning techniques.
JOURNAL OF LOW FREQUENCY NOISE VIBRATION AND ACTIVE CONTROL
(2021)
Article
Computer Science, Interdisciplinary Applications
Chun-yang Chen, Chao-Qun Xiang, Shu Cheng, Liu Zhi, Kaidi Li, Yating Chen, Xin Li
COMPUTING IN SCIENCE & ENGINEERING
(2020)
Article
Engineering, Electrical & Electronic
Xun Wu, Rui Tian, Shu Cheng, Tefang Chen, Li Tong
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2018)
Article
Computer Science, Interdisciplinary Applications
Kaidi Li, Chunyang Chen, Shu Cheng, Tianjian Yu, Chaoqun Xiang, Xun Wu
COMPUTING IN SCIENCE & ENGINEERING
(2019)
Article
Engineering, Electrical & Electronic
Xun Wu, Chun-Yang Chen, Te-Fang Chen, Shu Cheng, Zhi-Hong Mao, Tian-Jian Yu, Kaidi Li
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2020)
Article
Engineering, Electrical & Electronic
Kaidi Li, Shu Cheng, Tianjian Yu, Xun Wu, Chaoqun Xiang, Akin Bilal
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2020)
Article
Engineering, Electrical & Electronic
Chao-Qun Xiang, Xinan Zhang, Herbert Ho-Ching Iu, Lulin Zhang, Shu Cheng
Summary: This article proposes a novel duty ratio regulated virtual voltage vector model predictive torque control strategy for post-fault inverter fed induction motor drive with reduced neutral point voltage fluctuation. The method significantly improves steady-state torque control performance and reduces torque ripples and voltage fluctuations compared to conventional methods.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2021)
Proceedings Paper
Engineering, Industrial
Shu Cheng, Zhuoxin Li, Chaoqun Xiang, Lulin Zhang, Zekeng Ouyang
Summary: The proposed deadbeat direct torque control strategy effectively suppresses the fluctuation of the neutral-point potential (NPP) for the induction motor system driven by the eight switch three phase inverter. By synthesizing virtual zero vectors based on load current and NPP, the strategy achieves accurate control of torque and stator flux while also mitigating NPP fluctuations. Simulation results confirm the effectiveness of this method.
PROCEEDINGS OF THE 2021 IEEE 16TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2021)
(2021)
Article
Metallurgy & Metallurgical Engineering
Dai Yi, Cheng Shu, Gan Qin-jie, Yu Tian-jian, Wu Xun, Bi Fu-liang
Summary: A life prediction method based on linear Wiener process was proposed for Ni-Cd battery in electric multiple units (EMU), which showed accurate results for both monotonic and non-monotonic degraded systems. The study demonstrated that the binary linear Wiener degradation model based on capacity and energy has higher accuracy in predicting battery remaining useful life compared to the unary linear Wiener degradation model.
JOURNAL OF CENTRAL SOUTH UNIVERSITY
(2021)
Article
Computer Science, Information Systems
Shu Cheng, Lulin Zhang, Zhuoxin Li, Chaoqun Xiang
Summary: This paper proposes an improved segment direct torque control (DTC) method for high-power urban rail vehicles, aiming to achieve full speed range control. By utilizing different flux shapes in different speed ranges to reduce harmonic distortions, and introducing a transition control strategy, a smooth transition is achieved.
Proceedings Paper
Engineering, Electrical & Electronic
Chaoqun Xiang, Shu Cheng, Zhuoxin Li, Lulin Zhang
2020 IEEE 9TH INTERNATIONAL POWER ELECTRONICS AND MOTION CONTROL CONFERENCE (IPEMC2020-ECCE ASIA)
(2020)
Proceedings Paper
Engineering, Electrical & Electronic
Chaoqun Xiang, Xinan Zhang, Zhuoxin Li, Lulin Zhang, Shu Cheng
PROCEEDINGS OF THE 15TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2020)
(2020)
Article
Computer Science, Information Systems
Xun Wu, Te-Fang Chen, Shu Cheng, Tianjian Yu, Chaoqun Xiang, Kaidi Li
Proceedings Paper
Automation & Control Systems
Li Yufeng, Chen Tefang, Cheng Shu
2018 13TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA)
(2018)
Proceedings Paper
Automation & Control Systems
Zeng Boyang, Chen Tefang, Cheng Shu
2018 13TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA)
(2018)
