Article
Energy & Fuels
Yacine Terriche, Abderezak Lashab, Halil cimen, Josep M. Guerrero, Chun-Lien Su, Juan C. Vasquez
Summary: This paper proposes two developed open-loop algorithms for assessing the harmonics distortion of shipboard microgrids. These algorithms provide fast transient response and accurate analysis without relying on signal periodicity or frequency information. The algorithms are suitable for both short-term protective action and long-term preventive action stages.
Article
Automation & Control Systems
Przemyslaw Pietrzak, Marcin Wolkiewicz, Teresa Orlowska-Kowalska
Summary: This article proposes a novel approach for detecting and classifying faults in PMSM stator windings, using bispectrum analysis and convolutional neural network (CNN). Experimental results show that the proposed method achieves a classification effectiveness of 99.4%. Furthermore, the accuracy of the CNN model can be improved and the training time can be reduced by properly tuning the training parameters.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Chemistry, Multidisciplinary
Bilal Asad, Toomas Vaimann, Anouar Belahcen, Ants Kallaste, Anton Rassolkin, Payam Shams Ghafarokhi, Karolina Kudelina
Summary: This paper presents modeling and diagnostics of broken rotor bar fault by analyzing motor current with time-frequency analysis during extended startup transient time. The study utilizes nonstationary signal to segregate rotor faults and spatial harmonics, along with proposing an algorithm to improve spectrum legibility. Results show promising outcomes by efficient utilization of attenuation filter and consideration of maximum power spectral density area, based on machine's analytical model and measurements from laboratory setup.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Electrical & Electronic
Stephen Eduku, Qian Chen, Gaohong Xu, Guohai Liu, Jihong Liao, Xingwang Zhang
Summary: This article proposes a new fault-tolerant rotor permanent magnet flux-switching (FT-RPMFS) motor and proves its superior performance through comparison with conventional motors.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Article
Automation & Control Systems
Konstantinos N. Gyftakis, Antonio J. Marques Cardoso
Summary: The article explores diagnostic techniques for interturn faults and introduces a new method for monitoring stray flux to address the issue of traditional techniques being unable to accurately detect low-level interturn faults.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Energy & Fuels
Przemyslaw Pietrzak, Marcin Wolkiewicz
Summary: This paper discusses selected methods for detecting stator winding faults in permanent magnet synchronous motors, with effectiveness confirmed through experimental verification based on stator phase current signal analysis. The research distinguishes original fault indicators through observation of stator winding fault symptoms, showing which symptom is most sensitive to incipient faults in PMSMs.
Review
Engineering, Multidisciplinary
Gopika Lakshmi Priya Palla, Ajaya Kumar Pani
Summary: In process industries, early detection and diagnosis of faults using machine learning techniques is crucial for timely identification of process upsets, equipment and/or sensor malfunctions. This article reviews the basic technique of independent component analysis (ICA) as a viable alternative to principal component analysis, and presents a detailed survey of ICA-based techniques for process monitoring. The application of ICA in an industrial case study of multiphase flow system is illustrated, along with the selection of independent components by negentropy calculation and control limit and monitoring index calculation.
Article
Engineering, Biomedical
N. Gholamipour, F. Ghassemi
Summary: This study utilized Independent Component Analysis to automatically assess the reliability of components in EEG signals and found that the number of reliable components in the frequency domain is greater than that estimated in the time domain. Group-ICA algorithm was applied to ADHD/control groups to compare the validity of components between subjects, showing significant differences in the number of reliable components. Homogenous components in each group were determined by clustering.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Article
Computer Science, Information Systems
Raya A. K. Aswad, Bassim M. H. Jassim, Bashar Zahawi, Shady Gadoue
Summary: This paper presents a hybrid diagnostic system that combines a model-based strategy with a fuzzy logic classifier to identify abnormal motor states due to single-phasing or inter-turn stator winding faults. The proposed system only requires voltage and current measurements to extract fault symptoms and can effectively diagnose faults even in the presence of unbalanced supply voltages and measurement noise.
Article
Automation & Control Systems
Huan Qu, Z. Q. Zhu
Summary: This article proposes a design method for split-tooth stator slot permanent magnet machines with high fault-tolerant capability, demonstrating their advantages in increasing torque and demagnetization resistance through comparisons with existing models.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Energy & Fuels
Hisahide Nakamura, Keisuke Asano, Seiran Usuda, Yukio Mizuno
Summary: This study proposes a new diagnostic method for motor faults based on analyzing the sound characteristics of the motor during a no-load test. The research shows that characteristic signals appear periodically in a specific frequency range, and the effectiveness of diagnosing faults using deep learning methods has been verified through experiments.
Article
Engineering, Electrical & Electronic
Lei Ni, Chenguang Wang, Yanping Liang
Summary: As the demand for high efficiency and power density in ac motors grows, this article presents a method for detecting short-circuit faults in stator windings using transposition bars. By comparing the differences in the end leakage magnetic field between healthy and faulty bars, the functional relationship between the leakage magnetic field signal and the fault currents is established.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Materials Science, Multidisciplinary
Konrad Cyprych, Pawel Karpinski, Lech Sznitko, Andrzej Miniewicz, Jaroslaw Mysliwiec
Summary: Derivative analysis in spectroscopy is widely used, and it is particularly applicable to the analysis of multi-resonator laser emission. This study develops a numerical algorithm to simulate the laser action in a multi-resonator system and proposes an analytical protocol to enhance the accuracy of the analysis. By utilizing Fourier transforms and the nth derivatives of the laser emission spectra with respect to the wave-vector, this method can retrieve the size and Q-factor values of the optical resonators.
Article
Chemistry, Multidisciplinary
David Checa, Juan Jose Saucedo-Dorantes, Roque Alfredo Osornio-Rios, Jose Alfonso Antonino-Daviu, Andres Bustillo
Summary: The use of virtual reality (VR) as a training method offers a more engaging and interactive approach compared to traditional methods, especially for young students who are accustomed to continuous entertainment. This research focuses on the development of a VR-based application for teaching and training in the condition-based maintenance of induction motors, utilizing natural interactions with the VR environment. The usability of this VR tool has been validated with graduate and undergraduate students, demonstrating its suitability for both learning basic knowledge and practical skills related to induction motor maintenance.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Electrical & Electronic
Zeyu Liu, Bingyi Zhang, Yan Hu, Guihong Feng, Jiacheng Wu
Summary: This paper proposes a concave-core stator direct-drive permanent magnet motor (CCSDD-PMSM) structure to solve the problems mechanically caused by parallel direct-drive permanent magnet motors (DD-PMSM). An auxiliary yoke structure is proposed to optimize the magnetic circuit and analyze the cogging torque for achieving the minimum detent force. The stability characteristics of the motor are studied based on the unit motor and combined with the magnetomotive force.
IET ELECTRIC POWER APPLICATIONS
(2023)
Article
Energy & Fuels
Ting Yang, Haibo Pen, Dan Wang, Zhaoxia Wang
Article
Energy & Fuels
Ting Yang, Yingjie Zhao, Haibo Pen, Zhaoxia Wang
Article
Energy & Fuels
Ting Yang, Yajian Zhang, Zhaoxia Wang, Haibo Pen
Article
Computer Science, Artificial Intelligence
Zhaoxia Wang, Zhiping Lin
COGNITIVE COMPUTATION
(2020)
Review
Computer Science, Information Systems
Zhaoxia Wang, Seng-Beng Ho, Erik Cambria
MULTIMEDIA TOOLS AND APPLICATIONS
(2020)
Article
Computer Science, Artificial Intelligence
Zhaoxia Wang, Seng-Beng Ho, Erik Cambria
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS
(2020)
Article
Computer Science, Artificial Intelligence
Haibo Pen, Quan Wang, Zhaoxia Wang
Summary: Image analysis, particularly image restoration using SOMs, is a research focus in this paper. The proposed boundary precedence image inpainting method utilizes SOMs to separate damaged images into layers and calculates the filling order based on boundary precedence. The restoration process focuses on the boundary patches first for effective repair of both textural and structural information.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Jingfeng Cui, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria
Summary: Sentiment analysis, a research hotspot in natural language processing, has attracted significant attention and resulted in a growing number of research papers. Despite numerous literature reviews on sentiment analysis, there has been no dedicated survey examining the evolution of research methods and topics. This study fills this gap by conducting a comprehensive survey that combines keyword co-occurrence analysis and community detection algorithm. The survey compares and analyzes the connections between research methods and topics over the past two decades and uncovers hotspots and trends over time, providing valuable guidance for researchers. Furthermore, the paper offers practical insights, technical directions, limitations, and future research prospects in sentiment analysis.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Computer Science, Artificial Intelligence
Zhenda Hu, Zhaoxia Wang, Yinglin Wang, Ah-Hwee Tan
Summary: This paper introduces an improved model, MSRL-Net, for sentiment analysis task, which enhances sentence-level semantic representation by utilizing semantic relations between sentences. Compared to baseline models like BERT, MSRL-Net achieves significant improvements in accuracy, Macro-F1, and AUC.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Proceedings Paper
Computer Science, Information Systems
Zhaoxia Wang, Seng-Beng Ho, Zhiping Lin
2018 18TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW)
(2018)
Proceedings Paper
Computer Science, Artificial Intelligence
Yogesh Parth, Wang Zhaoxia
PROCEEDINGS OF ELM-2016
(2018)
Proceedings Paper
Computer Science, Information Systems
Zhaoxia Wang, Victor Joo Chuan Tong, Pingcheng Ruan, Fang Li
2016 IEEE 16TH INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW)
(2016)
Proceedings Paper
Computer Science, Artificial Intelligence
Zhaoxia Wang, Chee Seng Chong, Landy Lan, Yinping Yang, Seng Beng Ho, Joo Chuan Tong
PROCEEDINGS OF 2016 FUTURE TECHNOLOGIES CONFERENCE (FTC)
(2016)
Proceedings Paper
Computer Science, Artificial Intelligence
Zhaoxia Wang, Yogesh Parth
PROCEEDINGS OF ELM-2015, VOL 1: THEORY, ALGORITHMS AND APPLICATIONS (I)
(2016)