IEEE Transactions on Dielectrics and Electrical Insulation最新文献

{"title":"Online Fault Detection of Submarine DC Cables With Wide-Range Coverage","authors":"Longlei Bai;Jingyi Zeng;Liang Zou;Zejun Ma;Bo Luo;Jiang You;Xiaoxiong Cai;Hui Peng","doi":"10.1109/TDEI.2026.3686100","DOIUrl":"https://doi.org/10.1109/TDEI.2026.3686100","url":null,"abstract":"In recent years, long-term power failures of submarine DC cables caused by seawater erosion and anchor damage have posed increasing challenges to the safe and stable operation of underwater transmission systems. Accurate and efficient fault location is therefore essential for improving the reliability of submarine cable insulation. However, the conventional spread-spectrum time-domain reflectometry (SSTDR) method suffers from limited measurement efficiency and accuracy, as the chip duration of the modulation sequence constrains its detectable range. In this article, a mixed-modulation method is proposed to extend the effective measurement range of SSTDR. M-sequences with different chip durations are multiplied and modulated using binary phase shift keying (BPSK) with a sinusoidal carrier to form a mixed signal containing multiscale fault information. Based on theoretical analysis and experimental validation, submarine cable faults are simulated and analyzed for fault localization. The results show that the period of the m-sequence mixed is proportional to the measurement range, while the chip duration is positively correlated with the ranging blind zone. Based on this relationship, modulation experiments are conducted using m-sequences with chip durations of 1 and <inline-formula> <tex-math>$0.1~mu $ </tex-math></inline-formula>s. After mixed-modulation, the effective ranging interval is extended to 10.47–3245.70 m, compared with 104.70–3245.70 m and 10.47–324.57 m for the two individual sequences. In addition, the range of the blind zone is reduced. These results indicate that the proposed mixed-modulation method improves the applicability of SSTDR for submarine cable fault location.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"33 5","pages":"3777-3786"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149124557","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}

{"title":"Enhancing Severity Level Detection of Transformer Discharge and Thermal Faults Using Artificial Intelligence in Duval Triangle 1","authors":"Atul Jaysing Patil;Hasmat Malik;Arush Singh;Pranda Prasanta Gupta;Ram Naresh;Raj Kumar Jarial;Megha Atul Patil;Vaiju Kalkhambkar","doi":"10.1109/TDEI.2025.3650517","DOIUrl":"https://doi.org/10.1109/TDEI.2025.3650517","url":null,"abstract":"Interpreting incipient faults in mineral oil transformers using dissolved gas analysis (DGA) involves understanding the complex interrelationships in the evolution of various gases caused by different incipient faults. The Duval triangle 1 method is commonly used to interpret DGA results due to its wide acceptance; however, it still does not address the severity level of discharge and thermal (DT) incipient fault. This article focuses on understanding the relative concentration of different gases during DT and assigns a severity level with fault-space refinement by combining trusted graphical and synthetic data generation (SDG) techniques. DTs occur sparsely and require an SDG approach due to lack of real-world data related to different severity levels of DT faults. Integration of SDG techniques and analysis of key gas concentrations, such as methane and ethylene, critical fault thresholds is identified, with methane concentrations exceeding 43% indicating severe faults like <inline-formula> <tex-math>${T}3$ </tex-math></inline-formula> and <inline-formula> <tex-math>${D}2$ </tex-math></inline-formula>, while ethylene concentrations below 29% suggest low-to-medium thermal faults. Data instances 1113, 2 166 873, 13 989, 396 593, and 1 899 995 were identified for fault categories <inline-formula> <tex-math>${D}1$ </tex-math></inline-formula>, <inline-formula> <tex-math>${D}2$ </tex-math></inline-formula>, <inline-formula> <tex-math>${T}1$ </tex-math></inline-formula>, <inline-formula> <tex-math>${T}2$ </tex-math></inline-formula>, and <inline-formula> <tex-math>${T}3$ </tex-math></inline-formula> faults, respectively. Based upon rigorous analysis and training, the DT fault regions are segregated into different severity levels. This research offers a novel DT fault categorization which helps in condition monitoring of transformers.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"33 5","pages":"3920-3930"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149124594","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}

{"title":"The Effect of X-Ray Irradiation on the Electrical Characteristics and Microstructural Features of HVDC GIL/GIS Insulators","authors":"Feng Wang;Heng Yi;Lipeng Zhong;Yitong Hu;Kaibin Liang;Dexiong Hu;Yue Xia;Yi Xie;Zeping Huang;Yaoheng Xie","doi":"10.1109/TDEI.2026.3728396","DOIUrl":"https://doi.org/10.1109/TDEI.2026.3728396","url":null,"abstract":"X-ray irradiation is a feasible method for effectively dissipating surface charge on gas-insulated transmission system/pipeline (GIS/GIL) insulators without opening the enclosure, demonstrating great potential for engineering applications. However, whether the high-energy particles generated by X-ray irradiation affect solid insulating materials remains unknown. This study investigates the effects of key irradiation parameters, specifically tube voltage and irradiation duration, on the surface potential distribution, DC flashover voltage, dielectric constant, and surface molecular structure of epoxy composite insulating samples, aiming to explore the impact of X-ray exposure on the electrical characteristics and microstructural properties of insulators. Surface potential and flashover voltage tests conducted after X-ray irradiation indicate that when the tube voltage increases from 80 to 130 kV, surface charge accumulation decreases, and the flashover voltage increases. However, when the tube voltage further increases to 230 kV and the irradiation lasts for 60 min, X-ray exposure induces surface degradation, promoting the formation of amorphous and low-density regions on the sample surface. This modification alters the microstructure of the sample surface, thereby reducing surface charge accumulation and flashover voltage. Compared with unirradiated samples, the central surface potential and flashover voltage of irradiated samples decrease by 13.4% and 12.7%, respectively. These findings provide important experimental evidence supporting the engineering application of X-ray irradiation for surface charge dissipation in gas-insulated switchgear (GIS)/gas-insulated line (GIL) insulators.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"33 5","pages":"3324-3332"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149124560","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}

{"title":"Prediction of Degree of Polymerization of Insulating Paper in Transformer Hotspot Region Based on Dual Chemical Markers","authors":"Ruidong Rao;Jiefeng Liu;Heng Zhang;Zhuangzhuang Li;Ji Liu;Wen Li;Chuying Liu;Yongqing Lin","doi":"10.1109/TDEI.2026.3683367","DOIUrl":"https://doi.org/10.1109/TDEI.2026.3683367","url":null,"abstract":"Insulating paper in transformer winding hotspots represents the most vulnerable component of solid insulation systems, with its aging condition being critical for fault prediction. As key chemical markers for assessing the degree of polymerization (DP) of insulating paper, furfural and methanol concentrations (MCs) were measured through nonuniform thermal aging experiments. To address the limitations of conventional DP prediction models in capturing dynamic aging characteristics and achieving stable model optimization, a DP prediction framework is proposed by integrating dynamic dual chemical markers with an extreme gradient boosting (XGBoost) model optimized via a multistrategy enhanced escape (MSESC) algorithm. The concentrations and change rates of furfural and methanol, together with winding temperature, are used as model inputs, while the proposed MSESC algorithm improves global search stability and convergence efficiency in hyperparameter optimization. Experimental validation on 110 samples demonstrated the proposed model’s superiority, achieving a determination coefficient (R<inline-formula> <tex-math>${}^{{2}}text {)}$ </tex-math></inline-formula> of 0.99. SHAP analysis further identified MC, furfural concentration, and winding temperature as dominant factors influencing DP. The MSESC-XGBoost model significantly advances DP prediction accuracy and provides robust support for transformer insulation condition assessment.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"33 5","pages":"3617-3626"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149124583","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}

{"title":"Joint Sparse Dictionary Learning Method for Multimode Parameters of Distribution Transformer PD Signals","authors":"Shice Zhao;Yuehan Qu;Kaiyun Wen;Guang Han;Mingming Wang","doi":"10.1109/TDEI.2026.3656862","DOIUrl":"https://doi.org/10.1109/TDEI.2026.3656862","url":null,"abstract":"Partial discharge (PD) can characterize and affect the insulation performance of distribution transformers. However, PD signals have the problem of a single-mode sparse dictionary with a single task and high computational complexity. Therefore, a joint sparse dictionary learning method for multimode parameters of PD signals of distribution transformers (PD-MJSR) is proposed. PD-MJSR supports the establishment of a unified sparse dictionary based on the joint sparse representation (JSR) of the multimodal parameters of PD signals. PD-MJSR includes two algorithms to collaborative training heterogeneous mode parameters. First, an adaptive Log-Det regularized multimode metric learning algorithm is proposed for the multimode parameters of PD signals. This improves dictionary compactness and classification performance while preserving high-dimensional information. After that, a Lévy flight-based dictionary training algorithm is proposed to improve the global search ability and dictionary learning efficiency. The results show that PD-MJSR enables the joint dictionary to have multitask properties and improves sample utilization and task performance. The sample size required for training is 42.86% of similar methods, and the classification and reconstruction accuracies reach 96.5% and 0.84, respectively. PD-MJSR supports the flexible selection of mode parameters of PD signals and can meet the requirements of multitasks such as compression measurement and pattern recognition.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"33 5","pages":"3676-3685"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149125446","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}

{"title":"Thermal Performance Analysis of Retrofilled Power Transformers","authors":"Ismael Antolin;Agustin Santisteban;Inmaculada Fernandez;Mert Koçanali;Caner Adişen;Alfredo Ortiz;Francisco de Leon","doi":"10.1109/TDEI.2026.3707522","DOIUrl":"https://doi.org/10.1109/TDEI.2026.3707522","url":null,"abstract":"This article presents a thermo-hydraulic performance analysis of retrofilled power transformers assessed with computational fluid dynamics-finite element method (CFDs–FEM) simulations. A 14 MVA transformer winding was modeled to evaluate the effect of residual mineral oil (MO) on temperature and velocity fields when replaced with natural ester (NE) and synthetic ester (SE). Four degrees of retrofilling were considered (2.5%, 5%, 7.5%, and 10% residual MO), along with reference cases (two types of MOs, and a synthetic and NE). The increase in residual MO leads to minor thermo-hydraulic variations in the maximum temperature and fluid velocity. This indicates that cooling performance remains practically unchanged from an engineering standpoint. Despite the negligible thermal effect, residual MO content substantially reduces the fire point of esters, which results in loss of IEC K-class classification. Similarly, the biodegradability advantage of ester fluids (>90%) is progressively diminished when mixed with MO (<30%). The findings reinforce the need for careful control of MO extraction during retrofilling procedures to fully preserve the intended operational and environmental advantages of ester dielectric liquids.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"33 5","pages":"3949-3957"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11580367","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149125468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adsorption Performance and Numerical Simulation of Charged Particle Trajectory of IFD Electrostatic Filter Under Electric-Flow Multiphysical Coupling Fields","authors":"Chenyang Liu;Tao Li;Xiaoquan Zheng","doi":"10.1109/TDEI.2026.3702968","DOIUrl":"https://doi.org/10.1109/TDEI.2026.3702968","url":null,"abstract":"In this article, a new type of air purification product, intense field dielectric (IFD) electrostatic filter, is studied on the trajectory of charged particles under the electric-flow coupling fields. The electric field model optimization and the electric-flow field simulation of the IFD insulation structure were carried out by COMSOL. The simulation results show that the electric field distribution in the IFD channel is relatively symmetrical, and the average electric field in most areas is about 2.45 kV/mm. The flow field distribution shows that the flow velocity distribution is consistent in the middle of the IFD channel, while the flow velocity at the entrance presents a trend of first rising and then decreasing. The trajectory of charged particles is closely related to particle size, wind speed, and applied DC voltage. The capture probability increases with the increase in particle size and decreases with the increase in wind speed. Finally, the IFD electrostatic filter sample was prepared, and the high-voltage electrostatic adsorption test was carried out. The test results showed that the overall wind resistance of the IFD electrostatic filter was only 6.4 Pa, and the adsorption efficiency of <inline-formula> <tex-math>$2~mu $ </tex-math></inline-formula>m particles could reach 95.7%, respectively. The adsorption efficiency increased with the increase in the charged particle size. The developed IFD product with a high PM2.5 adsorption efficiency can be applied in the future industrial field widely.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"33 5","pages":"3466-3475"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149125499","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}

{"title":"Machine Learning and Molecular Simulation Driven Design of Antioxidants for Ester Insulation Oils","authors":"Yihua Qian;Tingyu Sun;Qing Wang;Qibin Xia;Hongxia Xi","doi":"10.1109/TDEI.2025.3636106","DOIUrl":"https://doi.org/10.1109/TDEI.2025.3636106","url":null,"abstract":"Antioxidants are critical additives in both petroleum and bio-based ester insulating oils as they inhibit oxidative degradation and extend fluid life. In this study, 91 antioxidant derivatives are designed by integrating machine learning (ML) and molecular simulation, aiming to enhance their practical applications in power systems. Key antioxidant descriptors-including Frontier molecular orbitals energy gap (HOMO-LUMO gap), the minimum absolute charge of the hydrogen atom (Abs_H_Charge), and ionization potential (IP)-are analyzed to assess antioxidant performance. Among these derivatives, VE_CN_3 (functionalized vitamin-E by cyano group at the third active site) is identified as the most promising candidate, demonstrating superior oxidative stability. To further predict antioxidant performance, 12 ML regression models are developed using the key molecular descriptors. Among these models, random forest (RF) and gradient boosting (GBoost) exhibit the highest predictive accuracies (with <inline-formula> <tex-math>${R}^{{2}}$ </tex-math></inline-formula> achieving 0.83), highlighting the potential of ML in capturing the relationship between molecular structure and antioxidant efficacy. The SHapley Additive exPlanations (SHAPs) analysis further reveals that specific molecular features, such as discontinuous methylene groups and ring structures, play critical roles in influencing antioxidant performance. Future research will aim to expand the molecular dataset to further validate and refine the predictive models, including the incorporation of a more comprehensive range of antioxidant functional groups and additional physicochemical parameters directly relevant to hydrogen atom transfer (HAT) and single electron transfer (SET) mechanisms. Furthermore, in order to rigorously assess metalantioxidant interactions and corrosion effects, subsequent studies will integrate descriptors related to metal coordination propensity and evaluate candidate molecules through accelerated aging experiments employing copper and silver strips.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"33 5","pages":"3065-3073"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149125520","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}

{"title":"Fault Diagnosis for 10-kV Cables Based on Improved WVD Algorithm and TG-MFN Framework","authors":"Bokai Liu;Lijun Zhou;Huajun Guan;Haibin Zhang;Yupeng Hu;Kejia Xu;Dongyang Wang;Guochao Qian","doi":"10.1109/TDEI.2026.3656260","DOIUrl":"https://doi.org/10.1109/TDEI.2026.3656260","url":null,"abstract":"The 10-kV power cable constitutes a critical component in urban power grids, with fault diagnosis primarily comprising fault location and insulation damage assessment. Time–frequency-domain reflectometry (TFDR) is widely employed for cable fault diagnosis. However, cross-term artifacts and inadequate feature extraction significantly impact the accuracy of both location and assessment processes. This article presents a comprehensive approach to address these challenges. First, we optimize the Wigner–Ville distribution (WVD) using adaptive threshold segmentation to mitigate cross-term artifacts during TFDR data processing. Second, we implement a propagation-based amplitude compensation algorithm to eliminate distance-dependent attenuation, followed by extracting features from time-domain excitation responses and energy spectrograms using a three-stage progressive feature selection strategy. Finally, we propose a transformer-gated multifeature network (TG-MFN) framework that integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Transformer-style adaptive attention gating mechanisms. This integration enables precise fault severity assessment through multiscale feature extraction and dynamic feature importance adjustment. The results show that the proposed method achieves: 1) effective elimination of cross-term interference, with insulation damage fault localization errors controlled within 1.44% and 2) precise severity assessment, with the maximum assessment error not exceeding two severity levels, enabling precise evaluation of insulation damage severity.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"33 5","pages":"3766-3776"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149125515","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}

{"title":"Lifespan Evaluation and Reliability-Oriented Design of Deep-Sea Motor Considering Cyclic Thermomechanical Stress","authors":"Jian Zhang;Zhenbo Yan;Yutong Zhou;Jiajin Wang;Rui Wang;Kangwen Wu;Xiangning He;Jianwei Wu","doi":"10.1109/TDEI.2026.3714384","DOIUrl":"https://doi.org/10.1109/TDEI.2026.3714384","url":null,"abstract":"Deep-sea motors play a critical role in oceanographic exploration, where operational reliability is of paramount importance. Conventional reliability analysis methods, primarily developed for insulation failure under constant stress in atmospheric conditions, are inadequate under high-hydrostatic pressure and variable load, typical of deep-sea environments. To address this issue, a lifetime prediction framework is proposed, which incorporates pressure fluctuations and current variations as key influencing factors. A thermomechanical stress model is first established and experimentally validated, yielding a simulation error of 9.3%. The pseudolifetime under cyclic stress is estimated using the observed dielectric-loss degradation trajectories. A refined lifetime prediction model is then formulated based on a modified Coffin–Manson relation, achieving a prediction error within 5%. To support a reliability evaluation under dynamic load conditions, a lumped parameter thermal network (LPTN) model is introduced to characterize the mapping between current input and the winding hot-spot temperature. Based on these, a parameterized current–depth–lifetime correlation framework is established. By determining the winding hot-spot temperature, the motor reliability and power density are optimized.","PeriodicalId":13247,"journal":{"name":"IEEE Transactions on Dielectrics and Electrical Insulation","volume":"33 5","pages":"3842-3851"},"PeriodicalIF":3.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149125557","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}