IEEE Transactions on Dielectrics and Electrical Insulation最新文献_第7页

Aging Failure Mechanism of Graft Modified Polypropylene Cable Insulation 接枝改性聚丙烯电缆绝缘老化失效机理研究

IF 3.1 3区工程技术

IEEE Transactions on Dielectrics and Electrical Insulation Pub Date : 2025-02-18 DOI: 10.1109/TDEI.2025.3543154

Yunjian Wu;Danfeng Zhang;Yifan Guo;Fanwu Chu;Guangke Li;Xiaoxing Zhang

{"title":"Aging Failure Mechanism of Graft Modified Polypropylene Cable Insulation","authors":"Yunjian Wu;Danfeng Zhang;Yifan Guo;Fanwu Chu;Guangke Li;Xiaoxing Zhang","doi":"10.1109/TDEI.2025.3543154","DOIUrl":"https://doi.org/10.1109/TDEI.2025.3543154","url":null,"abstract":"The performance of polypropylene (PP) insulation material used in high-voltage power cables is crucial for ensuring the safe and reliable operation of the cables. To deeply understand the aging and failure mechanisms of graft-modified PP cable insulation, accelerated aging experiments were conducted on the cable insulation layer. The ac breakdown field strength and elongation at break were tested, the density functional theory calculations were performed on the graft-modified PP molecular chains, and further analyses of the physicochemical properties, such as the microstructure and molecular structure changes of the insulation material, were conducted. The results show that when the insulation material reaches the aging failure point, the breakdown performance significantly decreases, the perfection of the crystalline region structure of PP deteriorates with aging time, the content of C=O carbonyl groups significantly increases with aging time, and thermal-oxidative aging accelerates the destruction of PP spherulites. The appearance of oxidation products, structure loosening, and decreased crystallinity during the aging process are the main reasons for the reduction in mechanical performance and breakdown strength. This study provides new insights into the research on the aging mechanism, structure, and performance relationship of PP cable insulation and has important guiding significance for the design of PP insulation materials.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"32 4","pages":"2205-2212"},"PeriodicalIF":3.1,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of the DC–AC Switching Electric Field on Surface Electrical Properties of GIS Epoxy Spacer 直流-交流开关电场对GIS环氧树脂隔层表面电学性能的影响

IF 3.1 3区工程技术

IEEE Transactions on Dielectrics and Electrical Insulation Pub Date : 2025-02-17 DOI: 10.1109/TDEI.2025.3543146

Song Yanze;Zhang Yutong;Xie Jun;Liang Guishu;Ran Huijuan;Zhong Yuyao;Xia Guowei;Zhang Minhan;Zhang Zhenli;Xie Qing

引用次数: 0

Transformer Dissolved Gas Concentration Prediction Based on Quadratic Decomposition Reconstruction and BKA-BiLSTM 基于二次分解重构和BKA-BiLSTM的变压器溶解气体浓度预测

IF 3.1 3区工程技术

IEEE Transactions on Dielectrics and Electrical Insulation Pub Date : 2025-02-14 DOI: 10.1109/TDEI.2025.3542749

Can Ding;Donghai Yu;Xianqiao Li;Daomin Min

{"title":"Transformer Dissolved Gas Concentration Prediction Based on Quadratic Decomposition Reconstruction and BKA-BiLSTM","authors":"Can Ding;Donghai Yu;Xianqiao Li;Daomin Min","doi":"10.1109/TDEI.2025.3542749","DOIUrl":"https://doi.org/10.1109/TDEI.2025.3542749","url":null,"abstract":"For the prediction of each gas concentration in oil-immersed transformers, in this article, improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is first applied to the original gas data, and the sample entropy (SE) value of each subsequence is computed, the high-frequency sequences with the highest SE are subjected to quadratic variational mode decomposition (VMD) to further reduce the degree of its instability, that is, the ICEEMDAN-SE-VMD decomposition model is formed. Second, reconstruction operations are performed on the subsequences with close SE values after ICEEMDAN decomposition to reduce the prediction time while ensuring the accuracy. Finally, a bidirectional long short-term memory with attention mechanism (Bi-LSTM-AT) is used to predict each subsequence separately; for the optimization of the parameters in prediction algorithms, the latest black-winged kite algorithm (BKA) is used in this article for optimization of the parameters, and the prediction results of the subsequence are superimposed to be the final prediction value for the gas concentration. The prediction results of the six gases produced by the transformer show that compared with other methods, the prediction method used in this article reduces the prediction time, while the prediction accuracy is also guaranteed.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"32 4","pages":"2433-2442"},"PeriodicalIF":3.1,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid Deep Learning Models for Enhanced Classification of Phase-Resolved Partial Discharge Patterns From High-Voltage Rotating Machine Insulation 基于混合深度学习模型的高压旋转电机绝缘相位分辨局部放电模式增强分类

IF 3.1 3区工程技术

IEEE Transactions on Dielectrics and Electrical Insulation Pub Date : 2025-02-14 DOI: 10.1109/TDEI.2025.3542343

Ciptian Weried Priananda;Hazlee Azil Illias;Wong Jee Keen Raymond;I. Made Yulistiya Negara

{"title":"Hybrid Deep Learning Models for Enhanced Classification of Phase-Resolved Partial Discharge Patterns From High-Voltage Rotating Machine Insulation","authors":"Ciptian Weried Priananda;Hazlee Azil Illias;Wong Jee Keen Raymond;I. Made Yulistiya Negara","doi":"10.1109/TDEI.2025.3542343","DOIUrl":"https://doi.org/10.1109/TDEI.2025.3542343","url":null,"abstract":"Partial discharge (PD) monitoring plays a crucial role in identifying insulation defects in high-voltage rotating machinery, where accurate classification is essential for improving the reliability and efficiency of condition-based maintenance (CBM). This work proposes hybrid convolutional neural network (CNN) models to classify phase-resolved PD (PRPD) patterns from six different defects in a rotating machine insulation. Various hybrid models were evaluated by integrating CNN with machine learning (ML) algorithms, which include support vector machines (SVMs), k-nearest neighbors (KNNs), logistic regression (LR), decision trees (DTs), random forests (RFs), and naive Bayes (NB). The results reveal that all proposed hybrid models consistently outperform CNN in terms of computational efficiency, by achieving an average accuracy of 94.87% across all models using two optimizers, ADAM and stochastic gradient descent with momentum (SGDM). Notably, CNN-RF (CNN-RF) and CNN-KNN (CNN-KNN) models achieve the best performance, with an accuracy exceeding 96% with lower computational time compared to CNN, which only achieves 94.44% accuracy. Thus, this work provides valuable insight into enhancing PRPD classification with lower computational cost while increasing the classification accuracy of PRPD patterns from rotating machine insulation.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"32 5","pages":"3059-3067"},"PeriodicalIF":3.1,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dielectric Mechanisms and Health State Estimation for High-Voltage XLPE Cable Insulation Under Nonuniform Thermal Aging 非均匀热老化下高压交联聚乙烯电缆绝缘介电机理及健康状态评估

IF 3.1 3区工程技术

IEEE Transactions on Dielectrics and Electrical Insulation Pub Date : 2025-02-14 DOI: 10.1109/TDEI.2025.3542752

Xize Dai;Jian Hao;Mohamed El Moursi;Rongxin Chen;Ruijin Liao;Claus Leth Bak

{"title":"Dielectric Mechanisms and Health State Estimation for High-Voltage XLPE Cable Insulation Under Nonuniform Thermal Aging","authors":"Xize Dai;Jian Hao;Mohamed El Moursi;Rongxin Chen;Ruijin Liao;Claus Leth Bak","doi":"10.1109/TDEI.2025.3542752","DOIUrl":"https://doi.org/10.1109/TDEI.2025.3542752","url":null,"abstract":"High-voltage (HV) crosslinked polyethylene (XLPE) cables are subjected to electrothermal stress gradients during service, which often leads to nonuniform degradation within insulation systems, significantly affecting their endurance, resilience, and overall lifetime. This article presents a comprehensive study of dielectric mechanisms and health state estimation of XLPE insulation under nonuniform thermal aging, with a particular emphasis on 500-kV XLPE cables. First, the distinct effects of uniform versus nonuniform thermal aging mechanisms on XLPE systems are compared through selected five combinations in two groups. Furthermore, the mechanisms by which nonuniform thermal aging influences XLPE insulation systems are revealed using three dielectric analysis techniques. Additionally, this work innovatively introduces a quantitative framework for the health state estimation of XLPE cable insulation under nonuniform thermal aging, utilizing the previously developed equivalent circuit model that incorporates a fractional-order circuit module (FOCM). The aging features extracted from the FOCM are utilized to develop health state estimation models for XLPE insulation under different nonuniform thermal aging conditions. The performance and limitations of health estimation models are discussed using a stacked XLPE system. This study deepens the understanding of nonuniform thermal aging mechanisms and provides insights to support condition-based maintenance of HV cable insulation under complex aging conditions.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"32 5","pages":"2868-2876"},"PeriodicalIF":3.1,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145189971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Temperature-Compensated CNN-Based Method for Transformer Partial Discharge Localization 基于温度补偿cnn的变压器局部放电定位方法

IF 3.1 3区工程技术

IEEE Transactions on Dielectrics and Electrical Insulation Pub Date : 2025-02-13 DOI: 10.1109/TDEI.2025.3542015

Haitao Wang;Shirong Zhang

引用次数: 0

Analytical Model for Transient Space Charge in Low-Density Polyethylene 低密度聚乙烯中瞬态空间电荷的解析模型

IF 2.9 3区工程技术

IEEE Transactions on Dielectrics and Electrical Insulation Pub Date : 2025-02-13 DOI: 10.1109/TDEI.2025.3541613

Purnabhishek Muppala;C. C. Reddy

{"title":"Analytical Model for Transient Space Charge in Low-Density Polyethylene","authors":"Purnabhishek Muppala;C. C. Reddy","doi":"10.1109/TDEI.2025.3541613","DOIUrl":"https://doi.org/10.1109/TDEI.2025.3541613","url":null,"abstract":"Despite being an experimentally well-studied phenomena, a consistent lacuna has always persisted in the theoretical and mathematical understanding of space charge dynamics in low-density polyethylene (LDPE). The macroscopic models reported so far in the literature seem to be insufficient and fail to predict the formation of homo- and hetero-charges near the electrodes and transport of charge packets. On the other hand, while microscopic models such as bipolar charge transport (BCT) model were able to explain homo-charge accumulation and movement of charge packets to a limited success, they are often fraught with assumptions such as neglection of diffusion phenomena and are structurally complicated when compared to macroscopic models. In this work, the authors have derived analytical solutions for space charge dynamics based on Maxwell’s equations and transient space charge limited current (TSLC)-based volumetric current models, which take into consideration the measured absorption (slow polarization) and steady-state volumetric currents. The proposed analytical (macroscopic) model can thus predict the homo- and hetero-charge accumulation in LDPE, which is validated through comparisons with the experimentally measured space charge, wherein a remarkable agreement was observed. Furthermore, the relation between the transient volumetric current and space charge dynamics is reaffirmed.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"32 3","pages":"1567-1574"},"PeriodicalIF":2.9,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing Insulator String Performance: Pollution and Icing Flashover Analysis Through Artificial Neural Network-Based Layout Optimization for Inverted T-Type String 提高绝缘子串性能：基于人工神经网络的倒t型串布局优化污染和覆冰闪络分析

IF 2.9 3区工程技术

IEEE Transactions on Dielectrics and Electrical Insulation Pub Date : 2025-02-13 DOI: 10.1109/TDEI.2025.3542009

Mahmoud A. Ali;Xingliang Jiang;Salah Kamel;Asad Awan

{"title":"Enhancing Insulator String Performance: Pollution and Icing Flashover Analysis Through Artificial Neural Network-Based Layout Optimization for Inverted T-Type String","authors":"Mahmoud A. Ali;Xingliang Jiang;Salah Kamel;Asad Awan","doi":"10.1109/TDEI.2025.3542009","DOIUrl":"https://doi.org/10.1109/TDEI.2025.3542009","url":null,"abstract":"This study explores the impact of various high-voltage insulator string configurations on pollution and icing flashover characteristics under different environmental conditions. The inverted T-string design is suggested, offering improvements over the traditional I-string configuration. An experimental investigation is conducted using high-voltage glass-type disks (LD-160), along with the development of two artificial neural network (ANN) models to simulate and predict flashover voltages. The results demonstrate that the inverted T-string arrangement enhances the flashover voltage for polluted insulator strings by approximately 7% and increases the icing flashover voltage by 3.43%–5.01% compared to standard I-strings. The ANN models successfully determine optimal insulator configurations, demonstrating their potential to enhance high-voltage insulation performance with minimal experimentation. This study emphasizes the innovative use of ANN in optimizing insulator string arrangements, providing a practical solution for tackling pollution and icing issues in power systems.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"32 3","pages":"1653-1659"},"PeriodicalIF":2.9,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spectral Analysis of Electrical Discharge in Mineral Oil—Comparison With Air Discharge 矿物油中放电的光谱分析——与空气放电的比较

IF 3.1 3区工程技术

IEEE Transactions on Dielectrics and Electrical Insulation Pub Date : 2025-02-13 DOI: 10.1109/TDEI.2025.3541615

Salma Nait Bachir;Azzeddine Nacer;Hocine Moulai;Issouf Fofana

{"title":"Spectral Analysis of Electrical Discharge in Mineral Oil—Comparison With Air Discharge","authors":"Salma Nait Bachir;Azzeddine Nacer;Hocine Moulai;Issouf Fofana","doi":"10.1109/TDEI.2025.3541615","DOIUrl":"https://doi.org/10.1109/TDEI.2025.3541615","url":null,"abstract":"This study aims to compare the spectral characteristics of electrical discharges in mineral oil (MO) with those in air. The results demonstrate that electrical discharge channels in MO exhibit a resistive nature, as evidenced by the phase difference, and that discharges in this medium are associated with higher energy levels due to their superior dielectric strength. This necessitates higher voltages for discharge initiation compared to electrical discharges in air, which involve lower energy levels due to air’s lower dielectric properties. Temporal domain analysis shows that electrical discharges in air propagate faster than those in MO. In addition, fast Fourier transform (FFT) analysis reveals that air discharges exhibit a broader spectrum with more high-frequency components, indicating faster propagation than MO discharges. The differences in dielectric properties—such as dielectric strength, breakdown voltage, density, and viscosity—are lower in the air than in MO, significantly influencing discharge characteristics, including current, voltage, power, and energy. These findings offer crucial insights into the nature of discharge channels, energy levels, propagation speeds, and discharge dynamics in air and MO. This contributes to developing more effective insulation monitoring and predictive maintenance strategies in electrical power systems.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"32 5","pages":"2788-2796"},"PeriodicalIF":3.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145190285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of Combined Current and Voltage Harmonics on the Thermal Behavior of Distribution Transformers: A Coupled Nonuniform Magnetic–Thermal Approach 电流和电压组合谐波对配电变压器热行为的影响：一种非均匀磁-热耦合方法

IF 3.1 3区工程技术

IEEE Transactions on Dielectrics and Electrical Insulation Pub Date : 2025-02-11 DOI: 10.1109/TDEI.2025.3540786

Ali Abdali;Akbar Bayat;Payam Javadi;Kazem Mazlumi;Abbas Rabiee

{"title":"Impact of Combined Current and Voltage Harmonics on the Thermal Behavior of Distribution Transformers: A Coupled Nonuniform Magnetic–Thermal Approach","authors":"Ali Abdali;Akbar Bayat;Payam Javadi;Kazem Mazlumi;Abbas Rabiee","doi":"10.1109/TDEI.2025.3540786","DOIUrl":"https://doi.org/10.1109/TDEI.2025.3540786","url":null,"abstract":"Since the insulation state and hotspot temperature (HST) are closely linked, monitoring the thermal condition of distribution transformers (DTs)—critical and costly power grid components—can help prevent failures. This study focuses on accurately predicting the HST in DTs. During the temperature rise test, optical fiber sensors (OFSs) are used to evaluate proposed nonuniform 3-D computational fluid dynamic (CFD)-based models. In contrast to the OFS measurements, the new 3-D CFD-based thermal study displays an error percentage of 0.11% (<inline-formula> <tex-math>$0.1~^{circ }$ </tex-math></inline-formula>C), indicating the high accuracy and efficiency of the model. Furthermore, the results of nonuniform 3-D CFD-based thermal assessments are validated using thermography for both top-oil temperature and bottom-oil temperature. With an error percentage of <0.65%,> <tex-math>$3.3~^{circ }$ </tex-math></inline-formula>C, <inline-formula> <tex-math>$7.1~^{circ }$ </tex-math></inline-formula>C, and <inline-formula> <tex-math>$10.3~^{circ }$ </tex-math></inline-formula>C more than the previous model without harmonics.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"32 4","pages":"2413-2423"},"PeriodicalIF":3.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0