Invasive techniques are becoming increasingly important in the presurgical evaluation of epilepsy. Adopting the electrophysiological source imaging (ESI) of interictal scalp electroencephalography (EEG) to localize the epileptogenic zone remains a challenge. The accuracy of the preoperative localization of the epileptogenic zone is key to curing epilepsy. The T1 MRI and the boundary element method were used to build the realistic head model. To solve the inverse problem, the distributed inverse solution and equivalent current dipole (ECD) methods were employed to locate the epileptogenic zone. Furthermore, a combination of inverse solution algorithms and Granger causality connectivity measures was evaluated. The ECD method exhibited excellent focalization in lateralization and localization, achieving a coincidence rate of 99.02% ( $p < 0.05$ ) with the stereo electroencephalogram. The combination of ECD and the directed transfer function led to excellent matching between the information flow obtained from intracranial and scalp EEG recordings. The ECD inverse solution method showed the highest performance and could extract the discharge information at the cortex level from noninvasive low-density EEG data. Thus, the accurate preoperative localization of the epileptogenic zone could reduce the number of intracranial electrode implantations required.
{"title":"Interictal Electrophysiological Source Imaging Based on Realistic Epilepsy Head Model in Presurgical Evaluation: A Prospective Study","authors":"Ruowei Qu;Zhaonan Wang;Shifeng Wang;Le Wang;Alan Wang;Guizhi Xu","doi":"10.23919/CJEE.2023.000012","DOIUrl":"10.23919/CJEE.2023.000012","url":null,"abstract":"Invasive techniques are becoming increasingly important in the presurgical evaluation of epilepsy. Adopting the electrophysiological source imaging (ESI) of interictal scalp electroencephalography (EEG) to localize the epileptogenic zone remains a challenge. The accuracy of the preoperative localization of the epileptogenic zone is key to curing epilepsy. The T1 MRI and the boundary element method were used to build the realistic head model. To solve the inverse problem, the distributed inverse solution and equivalent current dipole (ECD) methods were employed to locate the epileptogenic zone. Furthermore, a combination of inverse solution algorithms and Granger causality connectivity measures was evaluated. The ECD method exhibited excellent focalization in lateralization and localization, achieving a coincidence rate of 99.02% (\u0000<tex>$p < 0.05$</tex>\u0000) with the stereo electroencephalogram. The combination of ECD and the directed transfer function led to excellent matching between the information flow obtained from intracranial and scalp EEG recordings. The ECD inverse solution method showed the highest performance and could extract the discharge information at the cortex level from noninvasive low-density EEG data. Thus, the accurate preoperative localization of the epileptogenic zone could reduce the number of intracranial electrode implantations required.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 1","pages":"61-70"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10093776/10093783.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48470531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.23919/CJEE.2023.000001
Yunhao Yang;Heng Zhang;Shurong Peng;Sheng Su;Bin Li
Aiming at the wind power prediction problem, a wind power probability prediction method based on the quantile regression of a dilated causal convolutional neural network is proposed. With the developed model, the Adam stochastic gradient descent technique is utilized to solve the cavity parameters of the causal convolutional neural network under different quantile conditions and obtain the probability density distribution of wind power at various times within the following 200 hours. The presented method can obtain more useful information than conventional point and interval predictions. Moreover, a prediction of the future complete probability distribution of wind power can be realized. According to the actual data forecast of wind power in the PJM network in the United States, the proposed probability density prediction approach can not only obtain more accurate point prediction results, it also obtains the complete probability density curve prediction results for wind power. Compared with two other quantile regression methods, the developed technique can achieve a higher accuracy and smaller prediction interval range under the same confidence level.
{"title":"Wind Power Probability Density Prediction Based on Quantile Regression Model of Dilated Causal Convolutional Neural Network","authors":"Yunhao Yang;Heng Zhang;Shurong Peng;Sheng Su;Bin Li","doi":"10.23919/CJEE.2023.000001","DOIUrl":"https://doi.org/10.23919/CJEE.2023.000001","url":null,"abstract":"Aiming at the wind power prediction problem, a wind power probability prediction method based on the quantile regression of a dilated causal convolutional neural network is proposed. With the developed model, the Adam stochastic gradient descent technique is utilized to solve the cavity parameters of the causal convolutional neural network under different quantile conditions and obtain the probability density distribution of wind power at various times within the following 200 hours. The presented method can obtain more useful information than conventional point and interval predictions. Moreover, a prediction of the future complete probability distribution of wind power can be realized. According to the actual data forecast of wind power in the PJM network in the United States, the proposed probability density prediction approach can not only obtain more accurate point prediction results, it also obtains the complete probability density curve prediction results for wind power. Compared with two other quantile regression methods, the developed technique can achieve a higher accuracy and smaller prediction interval range under the same confidence level.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 1","pages":"120-128"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10093776/10093777.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49939763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.23919/CJEE.2023.000015
{"title":"Editorial for Special Issue on Bioelectromagnetics","authors":"","doi":"10.23919/CJEE.2023.000015","DOIUrl":"10.23919/CJEE.2023.000015","url":null,"abstract":"","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10093776/10093780.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48981694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gravity alterations in space cause significant adaptive effects on the human body, including changes to the muscular, skeletal, and vestibular systems. However, multiple factors besides gravity exist in space; therefore, it is difficult to distinguish gravity-related bioeffects from those of the other factors, including radiation. Although everything on the Earth surface is subject to gravity, gravity-induced effects are not explicitly clear. Here, different research methods that have been used in gravity alterations, including parabolic flight, diamagnetic levitation, and centrifuge, are reviewed and compared. The bioeffects that are reported to be associated with altered gravity in animals are summarized, and the potential risks of hypergravity and microgravity are discussed, with a focus on microgravity, which has been studied more extensively. It should be noted that although various microgravity and hypergravity research methods have their limitations, such as the inevitable magnetic field effects in diamagnetic levitation and short duration of parabolic flight, it is evident that ground-based clinical, animal, and cellular experiments that simulate gravity alterations have served as important and necessary complements to space research. These researches not only provide critical and fundamental biological information on the effects of gravity from biomechanics and the biophysical perspectives, but also help in developing future countermeasures for astronauts.
{"title":"Bioeffects of Microgravity and Hypergravity on Animals","authors":"Guofeng Cheng;Biao Yu;Chao Song;Vitalii Zablotskii;Xin Zhang","doi":"10.23919/CJEE.2023.000011","DOIUrl":"10.23919/CJEE.2023.000011","url":null,"abstract":"Gravity alterations in space cause significant adaptive effects on the human body, including changes to the muscular, skeletal, and vestibular systems. However, multiple factors besides gravity exist in space; therefore, it is difficult to distinguish gravity-related bioeffects from those of the other factors, including radiation. Although everything on the Earth surface is subject to gravity, gravity-induced effects are not explicitly clear. Here, different research methods that have been used in gravity alterations, including parabolic flight, diamagnetic levitation, and centrifuge, are reviewed and compared. The bioeffects that are reported to be associated with altered gravity in animals are summarized, and the potential risks of hypergravity and microgravity are discussed, with a focus on microgravity, which has been studied more extensively. It should be noted that although various microgravity and hypergravity research methods have their limitations, such as the inevitable magnetic field effects in diamagnetic levitation and short duration of parabolic flight, it is evident that ground-based clinical, animal, and cellular experiments that simulate gravity alterations have served as important and necessary complements to space research. These researches not only provide critical and fundamental biological information on the effects of gravity from biomechanics and the biophysical perspectives, but also help in developing future countermeasures for astronauts.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 1","pages":"29-46"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10093776/10093809.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41642785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.23919/CJEE.2023.000009
Hongbo Sun;Jianhua Liu;Qiuliang Wang
Magnetic actuation technology (MAT) provides novel diagnostic tools for the early screening and treatment of digestive cancers, which have high morbidity and mortality rates worldwide. The application of magnetic actuation systems and magnetic robots in gastrointestinal (GI) diagnosis and treatment to provide a comprehensive reference manual for scholars in the field of MAT research are reviewed. It describes the basic principles of magnetic actuation and magnetic field safety, introduces the design, manufacturing, control, and performance parameters of magnetic actuation systems, as well as the applicability and limitations of each system for different parts of the GI tract. It analyzes the characteristics and advantages of different types and functions of magnetic robots, summarizes the challenges faced by MAT in clinical applications, and provides an outlook on the future prospects of the field.
{"title":"Magnetic Actuation Systems and Magnetic Robots for Gastrointestinal Examination and Treatment","authors":"Hongbo Sun;Jianhua Liu;Qiuliang Wang","doi":"10.23919/CJEE.2023.000009","DOIUrl":"10.23919/CJEE.2023.000009","url":null,"abstract":"Magnetic actuation technology (MAT) provides novel diagnostic tools for the early screening and treatment of digestive cancers, which have high morbidity and mortality rates worldwide. The application of magnetic actuation systems and magnetic robots in gastrointestinal (GI) diagnosis and treatment to provide a comprehensive reference manual for scholars in the field of MAT research are reviewed. It describes the basic principles of magnetic actuation and magnetic field safety, introduces the design, manufacturing, control, and performance parameters of magnetic actuation systems, as well as the applicability and limitations of each system for different parts of the GI tract. It analyzes the characteristics and advantages of different types and functions of magnetic robots, summarizes the challenges faced by MAT in clinical applications, and provides an outlook on the future prospects of the field.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 1","pages":"3-28"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10093776/10093807.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45983539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A novel approach by introducing a statistical parameter to estimate the severity of incipient stator inter-turn short circuit (ITSC) faults in induction motors (IMs) is proposed. Determining the incipient ITSC fault and its severity is challenging for several reasons. The stator currents in the healthy and faulty cases are highly similar during the primary stage of the fault. Moreover, the conventional statistical parameters resulting from the analysis of fault signals do not consistently show a systematic variation with respect to the increase in fault intensity. The objective of this study is the early detection of incipient ITSC faults. Furthermore, it aims to determine the percentage of shorted turns in the faulty phase, which acts as an indicator for severe damage to the stator winding. Modeling of the motor in healthy and defective cases is performed using the Clarke Concordia transform. A discrete wavelet transform is applied to the motor currents using a Daubechies-8 wavelet. The statistical parameters $L_{1}$ and $L_{2}$ norms are computed for the detailed coefficients. These parameters are obtained under a variety of loads and defects to acquire the most accurate and generalized features related to the fault. Combining $L_{1}$ and $L_{2}$ norms creates a novel statistical parameter with notable characteristics to achieve the research aim. An artificial neural network-based back propagation algorithm is employed as a classifier to implement the classification process. The classifier output defines the percentage of defective turns with a high level of accuracy. The competency of the adopted methodology is validated via simulations and experiments. The results confirm the merits of the proposed method, with a classification test correctness of 95.29%.
{"title":"Stator Fault Diagnosis of Induction Motor Based on Discrete Wavelet Analysis and Neural Network Technique","authors":"Abdelelah Almounajjed;Ashwin Kumar Sahoo;Mani Kant Kumar;Sanjeet Kumar Subudhi","doi":"10.23919/CJEE.2023.000003","DOIUrl":"10.23919/CJEE.2023.000003","url":null,"abstract":"A novel approach by introducing a statistical parameter to estimate the severity of incipient stator inter-turn short circuit (ITSC) faults in induction motors (IMs) is proposed. Determining the incipient ITSC fault and its severity is challenging for several reasons. The stator currents in the healthy and faulty cases are highly similar during the primary stage of the fault. Moreover, the conventional statistical parameters resulting from the analysis of fault signals do not consistently show a systematic variation with respect to the increase in fault intensity. The objective of this study is the early detection of incipient ITSC faults. Furthermore, it aims to determine the percentage of shorted turns in the faulty phase, which acts as an indicator for severe damage to the stator winding. Modeling of the motor in healthy and defective cases is performed using the Clarke Concordia transform. A discrete wavelet transform is applied to the motor currents using a Daubechies-8 wavelet. The statistical parameters \u0000<tex>$L_{1}$</tex>\u0000 and \u0000<tex>$L_{2}$</tex>\u0000 norms are computed for the detailed coefficients. These parameters are obtained under a variety of loads and defects to acquire the most accurate and generalized features related to the fault. Combining \u0000<tex>$L_{1}$</tex>\u0000 and \u0000<tex>$L_{2}$</tex>\u0000 norms creates a novel statistical parameter with notable characteristics to achieve the research aim. An artificial neural network-based back propagation algorithm is employed as a classifier to implement the classification process. The classifier output defines the percentage of defective turns with a high level of accuracy. The competency of the adopted methodology is validated via simulations and experiments. The results confirm the merits of the proposed method, with a classification test correctness of 95.29%.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 1","pages":"142-157"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10093776/10093781.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46647461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.23919/CJEE.2023.000017
Hong Li;Zexi Zhou;Jinchang Pan;Qian Liu
For pulse-width modulated (PWM) DC-DC converters, the input voltage fluctuation and load variation in practical applications make it necessary for them to have better dynamic performance to meet the regulation requirements of the system. The dynamic-performance-improvement method for PWM DC-DC converters is mainly based on indirect dynamic performance indices, such as the gain margin and phase margin. However, both settling time and overshoot in the time domain are important in practical engineering. This makes it difficult for designers to obtain a clear understanding of the time-domain dynamic performance that can be achieved with improved control. In this study, a direct analysis of the time-domain dynamic characteristic of PWM DC-DC converters is performed. A dynamic-performance-improvement method based on eigenvalues and eigenvector sensitivity (E 2 S-based DPIM) is proposed to directly improve the time-domain dynamic performance index of PWM DC-DC converters. By considering a boost converter with proportional-integral control as an example, an additional virtual inductor current feedback control was designed using the proposed dynamic-performance-improvement method. Simulation and experimental results verify the validity and accuracy of the proposed dynamic-performance-improvement method.
{"title":"Time-domain Dynamic-performance-improvement Method for Pulse-width-modulated DC-DC Converters Based on Eigenvalue and Eigenvector Sensitivity","authors":"Hong Li;Zexi Zhou;Jinchang Pan;Qian Liu","doi":"10.23919/CJEE.2023.000017","DOIUrl":"10.23919/CJEE.2023.000017","url":null,"abstract":"For pulse-width modulated (PWM) DC-DC converters, the input voltage fluctuation and load variation in practical applications make it necessary for them to have better dynamic performance to meet the regulation requirements of the system. The dynamic-performance-improvement method for PWM DC-DC converters is mainly based on indirect dynamic performance indices, such as the gain margin and phase margin. However, both settling time and overshoot in the time domain are important in practical engineering. This makes it difficult for designers to obtain a clear understanding of the time-domain dynamic performance that can be achieved with improved control. In this study, a direct analysis of the time-domain dynamic characteristic of PWM DC-DC converters is performed. A dynamic-performance-improvement method based on eigenvalues and eigenvector sensitivity (E\u0000<sup>2</sup>\u0000S-based DPIM) is proposed to directly improve the time-domain dynamic performance index of PWM DC-DC converters. By considering a boost converter with proportional-integral control as an example, an additional virtual inductor current feedback control was designed using the proposed dynamic-performance-improvement method. Simulation and experimental results verify the validity and accuracy of the proposed dynamic-performance-improvement method.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 1","pages":"104-119"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10093776/10093782.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42492068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.23919/CJEE.2023.000014
Yuanyuan Li;Guoqiang Liu
Magnetic field and acoustic field coupled imaging methods mainly include magnetoacoustic tomography, magneto-acousto-electrical tomography, and thermoacoustic tomography, all of which non-invasively achieve the electrical conductivity imaging of tissues with a resolution of up to the millimeter scale. The principles of these three imaging methods and the research progress in the last two decades are reviewed. First, the principles of the three magnetic and acoustic field coupled methods are individually introduced. The progress in medical electromagnetic imaging is further elaborated, and finally the future directions and summary of the coupled imaging methods are summarized.
{"title":"A Review on the Coupled Method of Using the Magnetic and Acoustic Fields for Biological Tissue Imaging","authors":"Yuanyuan Li;Guoqiang Liu","doi":"10.23919/CJEE.2023.000014","DOIUrl":"10.23919/CJEE.2023.000014","url":null,"abstract":"Magnetic field and acoustic field coupled imaging methods mainly include magnetoacoustic tomography, magneto-acousto-electrical tomography, and thermoacoustic tomography, all of which non-invasively achieve the electrical conductivity imaging of tissues with a resolution of up to the millimeter scale. The principles of these three imaging methods and the research progress in the last two decades are reviewed. First, the principles of the three magnetic and acoustic field coupled methods are individually introduced. The progress in medical electromagnetic imaging is further elaborated, and finally the future directions and summary of the coupled imaging methods are summarized.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 1","pages":"47-60"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10093776/10093786.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43959018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An accurate extraction of vibration signal characteristics of an on-load tap changer (OLTC) during contact switching can effectively help detect its abnormal state. Therefore, an improved fuzzy C-means clustering method for abnormal state detection of the OLTC contact is proposed. First, the wavelet packet and singular spectrum analysis are used to denoise the vibration signal generated by the moving and static contacts of the OLTC. Then, the Hilbert-Huang transform that is optimized by the ensemble empirical mode decomposition (EEMD) is used to decompose the vibration signal and extract the boundary spectrum features. Finally, the gray wolf algorithm-based fuzzy C-means clustering is used to denoise the signal and determine the abnormal states of the OLTC contact. An analysis of the experimental data shows that the proposed secondary denoising method has a better denoising effect compared to the single denoising method. The EEMD can improve the modal aliasing effect, and the improved fuzzy C-means clustering can effectively identify the abnormal state of the OLTC contacts. The analysis results of field measured data further verify the effectiveness of the proposed method and provide a reference for the abnormal state detection of the OLTC.
{"title":"Abnormal State Detection of OLTC Based on Improved Fuzzy C-means Clustering","authors":"Hongwei Li;Lilong Dou;Shuaibing Li;Yongqiang Kang;Xingzu Yang;Haiying Dong","doi":"10.23919/CJEE.2023.000002","DOIUrl":"10.23919/CJEE.2023.000002","url":null,"abstract":"An accurate extraction of vibration signal characteristics of an on-load tap changer (OLTC) during contact switching can effectively help detect its abnormal state. Therefore, an improved fuzzy C-means clustering method for abnormal state detection of the OLTC contact is proposed. First, the wavelet packet and singular spectrum analysis are used to denoise the vibration signal generated by the moving and static contacts of the OLTC. Then, the Hilbert-Huang transform that is optimized by the ensemble empirical mode decomposition (EEMD) is used to decompose the vibration signal and extract the boundary spectrum features. Finally, the gray wolf algorithm-based fuzzy C-means clustering is used to denoise the signal and determine the abnormal states of the OLTC contact. An analysis of the experimental data shows that the proposed secondary denoising method has a better denoising effect compared to the single denoising method. The EEMD can improve the modal aliasing effect, and the improved fuzzy C-means clustering can effectively identify the abnormal state of the OLTC contacts. The analysis results of field measured data further verify the effectiveness of the proposed method and provide a reference for the abnormal state detection of the OLTC.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 1","pages":"129-141"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10093776/10093778.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45920661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Vibration and Noise Optimization of New Asymmetric Modular PMaSynRM","authors":"Guohai Liu;Akang Gao;Qian Chen;Yanxin Mao;Gaohong Xu","doi":"10.23919/CJEE.2023.000006","DOIUrl":"https://doi.org/10.23919/CJEE.2023.000006","url":null,"abstract":"","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7873788/10173479/10103785.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49982769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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