AC contactors are critical components in electrical automation systems, and accurately predicting their residual life is essential for improving system reliability. To address this, we propose a multi-model fusion framework that integrates ResNet18 for spatial feature extraction with LSTM for temporal sequence modeling, achieving accurate and stable RUL prediction of contactors. A dedicated experimental platform was built to conduct full electrical life tests and capture contact morphology images across all life stages, resulting in a complete dataset. To enhance model generalization and robustness, several data augmentation methods were applied, including scaling and cropping, rotation and flipping, adaptive brightness adjustment, and Gaussian noise. To overcome the limitations of conventional CNN-LSTM fusion models—such as weak feature extraction and degradation trend fitting—an improved model was developed by integrating three specialized feature extraction modules: composite scaling, depthwise separable convolution, and residual connections. The roles these modules are analyzed in detail. The proposed model was trained and evaluated the custom dataset. Performance was compared in terms of prediction accuracy, computational complexity, parameter count, and mean squared error (MSE). Results show that CNN-LSTM-ResNet18 model, with residual connections addressing gradient vanishing and information loss, achieves highest accuracy and meets practical engineering requirements.

This study investigates aging mechanisms of series‐connected batteries at low temperatures through multiscale analysis. A novel open‐circuit voltage (OCV) reconstruction method—which tracks voltage evolution during battery degradation—quantifies three distinct degradation modes: loss of lithium inventory (LLI), cathode active material (LAM PE ), and anode active material (LAM NE ). The method establishes direct correlations between electrochemical behavior and electrode morphology using 3D structural parameters. Results demonstrate that LLI dominates performance decay throughout battery life. LAM PE peaks during early cycles then stabilizes, while LAM NE accelerates in late‐stage aging. Strong linear relationships emerge between degradation patterns and morphological features, providing mechanistic insights into low‐temperature deterioration. Microscopic analyses (XRD, SEM, and EDS) confirm that cold conditions intensify the growth of the solid–electrolyte interphase and lithium plating, accelerating battery failure. This OCV‐based approach offers a nondestructive method for understanding degradation mechanisms in battery packs, advancing knowledge for cold‐climate battery applications.

With the expanding application of pulsed power technology in plasma physics, industrial processing, and defense and military weapon systems, the demand for compact and high-efficiency pulse generators has been steadily increasing. Conventional stacked Blumlein pulse generators (SBPGs) often suffer from limited voltage gain and low stacking efficiency due to electromagnetic coupling among transmission lines or parasitic coupling to ground. This paper presents a novel high-efficiency stacked Blumlein pulse generator that integrates a multi-stage Boost DC–DC converter with a magnetic coupling suppression method. The proposed approach directly embeds multiple nanocrystalline magnetic rings into a matching load or a small pre-load resistor, effectively increasing the coupling impedance and minimizing parasitic energy leakage. Meanwhile, the multi-Boost topology raises the charging voltage of each coaxial stage to several times the supply voltage, thereby achieving both enhanced voltage gain and improved stacking efficiency. Simulation and experimental results demonstrate that under a 400 V supply, each stage is charged to approximately 1.06 kV, producing an output voltage of 10 kV with a 49 ns rise time, 118 ns pulse width, and a stacking efficiency of 94.3%. This represents a 20% improvement over the case without the proposed method. The developed generator exhibits high gain, high efficiency, and wide tunability (20 kHz – 1 MHz), offering a promising solution for next-generation compact, solid-state, and high-repetition-rate pulsed power systems.

High-frequency transformers(HFTs) experience substantial thermal stress due to high operating frequencies and steep voltage gradients(dv/dt), leading to significant temperature rise. This thermal load accelerates material aging and increases the risk of insulation failure, which presents critical challenges for the development of HFTs in high-power, high-power-density applications. Effective thermal modeling is essential for optimizing HFT designs across large parameter spaces within limited timeframes. While thermal network models are attractive for their computational speed, enhancing their accuracy remains a key hurdle.This paper presents an advanced thermal network model that significantly improves accuracy by incorporating frequency-dependent effects and anisotropic heat conduction, modeled through specially defined thermal resistances. The model also computes temperature-dependent heat transfer coefficients across multiple planes to better capture the 3D thermal behaviour of HFTs. Validated against both simulations and experimental data, the proposed model achieves a hot-spot temperature error of just 3.31%. Compared with the thermal network model that ignores the frequency-dependent effect, its computational accuracy is improved by 1.43%, with a computation time of only 46 seconds; making its computation time only 1.23% of that of conventional experimentally validated finite element models. The combination of accuracy and efficiency makes the proposed model highly suitable for rapid HFT design optimization.

Air circuit breakers are critical protective devices in low-voltage distribution systems, and their reliability is considered to have significant influence on the operation of such systems. With respect to the electrical performance degradation of air circuit breakers, the relationship between the change in over-travel and the contact mass loss is analyzed, and a mechanical parameter method for the degree of contact erosion is proposed. The relationship between contact over-travel and the rotation angle of the pole shaft is investigated, and the monitoring of over-travel variation is achieved by measuring the pole shaft rotation angle. An electrical performance degradation model for air circuit breakers is established based on a univariate linear Wiener process with drift. The variation characteristics of the model parameters under different current stresses are analyzed, and a residual electrical life prediction method based on over-travel variation is developed. Electrical performance degradation experiments are conducted on air circuit breakers, from which the degradation model parameters are obtained. The residual electrical life is predicted using the over-travel variation data, and the relative prediction error is shown to be less than 5%. Real-time monitoring of the interrupting current and voltage waveforms of the air circuit breaker is not required by this method, which makes it convenient for practical engineering applications.

Achieving high reliability remains the critical challenge for pulsed power supplies (PPS), whose core components are susceptible to severe degradation and catastrophic failure due to long-term operation under electrical, thermal and magnetic stresses, particularly those associated with high voltage and high current. This reliability challenge fundamentally limits the widespread deployment of PPSs in defense and industrial applications. This article provides a comprehensive and systematic review of the reliability challenges and recent technological progress concerning PPSs, focusing on three hierarchical levels: component, system integration, and extreme operating environments. The review investigates the underlying failure mechanisms, degradation characteristics, and structural optimization of key components, such as energy storage capacitors and power switches. Furthermore, it elaborates on advanced system-level techniques, including novel thermal management topologies, jitter control methods for multi-module synchronization, and electromagnetic interference (EMI) source suppression and coupling path optimization. The primary conclusion is that achieving long-term, high-frequency operation depends on multi-physics field modeling and robust, integrated design approaches at all three levels. In summary, this review outlines important research directions for future advancements and offers technical guidance to help speed up the development of next-generation PPS systems characterized by high power density, frequent repetition, and outstanding reliability.

Accurate remaining useful life (RUL) prediction of AC contactors is essential for efficient operation and maintenance of the manufacturing system. Existing methods cannot adequately capture the degradation of AC contactors due to their inability to depict the special characteristic of zero and bounded arcing Joule integrals (i.e., degradation increments). To tackle this problem, the physical model of arcing Joule integrals is first derived through arcing mechanism analysis. Bounds of arcing Joule integrals are obtained by introducing critical breaking phase angles to the physical model, and four arcing modes are identified. A method for measuring the similarity between arcing modes is proposed, and then an arcing mode similarity based discrete-time Markov chain is constructed to depict arcing mode transitions. Motivated by zero and bounded arcing Joule integrals, an increment process with zero and bounded increments is proposed to characterize the degradation of a single-phase contact pair. Finally, the superiority of the proposed method is illustrated by real and numerical cases.

In this article, the long-chain branched polypropylene (LCBPP) synergistic blending method is proposed to improve the electrical and mechanical properties of polypropylene (PP)/polyolefin elastomer (POE) cable insulation. The results show that 5 wt% LCBPP, 40 wt% POE, and 55 wt% PP synergistic blending cable insulation material could reduce the leakage conductivity to 30.39%-46.24% at different temperatures. The breakdown strength is increased by 23.68%-33.98%. Furthermore, the tensile strength and elongation at break are increased by 20.46% and 16.88%, respectively. The LCBPP synergistic blending method could introduce deeper trap levels, contributing to adjusting carrier transport. Furthermore, the compatibility of PP and POE is improved. The research results provide a reference for the performance modification of PP/POE cable insulation.

Under different service conditions, low-voltage circuit breakers (LVCBs) present various failure modes, and it is necessary to discriminate these failure modes during reliability analysis. This paper addresses the issue of product reliability analysis under multiple failure modes, proposing a key failure mode discrimination method based on the ratio of the upper and lower limits of product's life (discrimination coefficient). The threshold of this mothed is independent of the failure distribution type, do not rely on expert experience, and are not limited to specific products. The relationship between the key failure modes of LVCBs and the current stresses is studied, and the critical current that causes the transition of key failure modes in LVCBs is researched, which can address the issue of discriminating the key failure modes of LVCBs under different service scenarios. Tests on LVCBs under different current stresses are conducted, and the failure distribution characteristic parameters at different currents are identified. A simplified reliability analysis model for LVCBs based on key failure modes is established. The accuracy of the key failure mode discrimination method and the simplified reliability analysis model is verified, providing a theoretical basis for assessing the reliability of LVCBs under different service conditions. (c) 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

The electric field intensity and space charge density are important parameters for gas discharge, and the study of the relationship between them not only helps to better understand the mechanism of corona discharge but also provides a reference for insulation margin design for power equipment. In this article, a space charge measurement platform based on the acoustic pulse method is constructed, and in this way, the distribution of space charge density in the corona cage can be obtained. In addition, corona discharge characteristics (including onset characteristics and electric field distribution) are obtained based on theoretical calculation and experimental measurement, and then the correlation mechanism between space charge and field intensity under dc voltage is established. The results show that when corona discharge occurs, the space charge density is positively correlated with the onset voltage and negatively correlated with the onset electric field, and the space charge is also negatively correlated with the surface electric field intensity around the wire surface. However, the space charge density gets bigger with the increase of spatial electric field intensity in the corona cage. The above research results can reveal the correlation mechanism between space charge and electric field intensity more accurately, which is of great significance for the in-depth study of the corona discharge mechanism and air discharge characteristics.

Accurate remaining useful life prediction is crucial for prognostics and health management of products. Model uncertainty is an important factor negatively affecting prediction performance. Existing methods fail to evaluate the predictive ability of a degradation model without the actual remaining useful life, and typically require adequate degradation data or prior information. They may be unable to ensure a reliable prediction performance in practical engineering scenarios with limited degradation data and mechanism knowledge. To address these issues, a model fusion based method is proposed using the uncertainty theory. Specifically, a comprehensive model performance evaluation method is proposed by simultaneously considering complexity, fitting ability, and predictive ability. The evolution process of the comprehensive model performance index is modelled by proposing a generalized arithmetic Liu process model that can flexibly depict characteristics of an uncertain process. A model fusion method is proposed by quantifying the similarity between a candidate model and the actual degradation process based on the predictive evolution analysis of the performance index. Then, a random initial solutions based algorithm is proposed to estimate remaining useful life from the fused model. Finally, three real cases and a numerical case are utilized to demonstrate the effectiveness and versatility of the proposed method by comparing it with existing methods.

During the current breaking period of low-voltage DC circuit breakers, their contacts and arc extinction system are eroded by arc combustion. The morphology of the arc plate significantly changes after arc erosion. On this basis, a service times prediction model of low-voltage DC circuit breaker is proposed. First, by observing the morphological changes of the arc plates, it is found that a bright metal fusion trace appears on their surface. With increasing occurrence of arc erosion, significant material loss appears at the top of the arc plates. Then, the grayscale transformation enhancement and region growth algorithms are proposed to preprocess and segment the morphological image of the arc plate to obtain the metal fusion trace. An image mask processing method is proposed to extract the contour of the arc plate to obtain the material loss area. Finally, the two morphological features of the arc plate are used as degradation indicators for low-voltage DC circuit breakers, establishing a service times prediction model based on Gaussian process regression. Through experimental verification, the relative errors between the predicted and true values of the current service times are verified to be less than 20%. (c) 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

This paper selects two types of polypropylene/elastomer blended commercial cable main insulation materials. Accelerated thermo-oxidative aging experiments at 135° C are carried out. The influence of thermo-oxidative aging on the macroscopic morphology, physicochemical properties, dielectric loss, frequency breakdown field strength and other parameters of the two types of polypropylene insulation is compared and analyzed. The evolution of the electrical performance of polypropylene blended insulation under thermo-oxidative aging is revealed. The test results show that at higher temperatures, low-melting-point elastomer may agglomerate and migrate, leading to the destruction of the sea-island structure of polypropylene and elastomer, resulting in a decrease in the tensile properties of polypropylene blended insulation.

Polydopamine-coated silica nanopowder SiO 2 @PDA was prepared, and SiO 2 @PDA powder and polypropylene (PP) substrate were melt blended by melt mixing method to obtain SiO 2 @PDA-modified polypropylene cable materials. SEM test, X-ray diffraction (XRD) test, breakdown field strength test, dielectric constant test and oxidation induction period test were performed. The results showed that PDA-coated SiO 2 nanoparticles improved the interfacial compatibility of SiO 2 nanoparticles with polypropylene matrix and the dispersion of SiO 2 nanoparticles in the main insulating material of polypropylene cables. Blending modification of PP cable main insulators using SiO 2 @PDA powder can enhance the electrical properties and heat and oxygen aging resistance of PP cable main insulators.

In this paper, a modification method using polydopamine (PDA) to modulate the properties of polypropylene (PP) is presented. PDA was synthesized, and PP composites with PDA additions of 0.1 wt.%, 0.3 wt.%, and 0.5 wt.% were prepared by melt blending method. The PP was characterized by Fourier Infrared Spectrometer (FIR). The properties of PP samples were analyzed by a series of methods, including scanning electron microscopy (SEM), X-ray diffraction (XRD), DC breakdown test, broadband impedance test, and oxidation-induced period test (OIT). The results showed that the introduction of PDA into PP promoted the generation of beta-crystals. The composites exhibited a significant enhancement in electrical properties and thermo-oxidative stability compared to unmodified PP samples. 0.3 wt.% PDA-PP showed the best breakdown performance, with the characteristic breakdown field strength increasing by 25.1 kV/mm compared to pure PP. The OIT value increased with the rising amount of PDA added, and the OIT value of 0.5 wt.% PDA-PP was prolonged by 17.1 min relative to pure PP.

In the breaking current process, low-voltage DC circuit breakers inevitably generate arc. Arc ablation will seriously affect the health status of circuit breakers. Therefore, this paper proposed a health status evaluation method of lowvoltage DC circuit breakers based on the morphological features of arc plate, by analyzing the arc erosion traces. Firstly, carry out the cyclic operation test of DC circuit breaker, and collect the 2-D morphology image of arc plate at a certain interval. Then, the image processing algorithm is used to visualize the arc guide image. The key morphological feature parameters are extracted: 1) Distinguish the color difference between the arc track area and other areas through the threshold segmentation method. Thus, the arc track area is extracted and its area is calculated as feature h(1); 2) Extract the material loss area of arc plate after ablation based on unablated image. Thus, the loss area is calculated as feature h(2). Finally, according to the degradation trajectories of features h1 and h2, they are divided into linear degradation features and nonlinear degradation features. This paper established a health status assessment model using both segmented fitting and sigma principle. Through example verification, the accuracy of this model is as high as 100 %. By using the morphological characteristics of arc plate, the purpose of characterizing health status of circuit breaker is achieved.

Real-time assessment of ground-wall (GW) insulation condition is critical for the reliable operation of inverter-fed motors (IFMs) and many online monitoring methods have been proposed. However, the existing methods can only detect the overall insulation degradation condition, the refined assessment of degradation position is rarely reported. In this article, a diversified assessment method is proposed that can identify the severity, position, and phase of GW insulation degradation by using the transient characteristics of leakage current. A stator winding insulation model is established to analyze the relationship between leakage current and GW insulation in IFMs. After the theoretical analysis, the common-mode harmonic and differential-mode harmonic of leakage current are utilized to identify the severity and position of GW insulation degradation, respectively. Moreover, the initial oscillation amplitude of the leakage current is used to assess the degradation phase of GW insulation. The proposed method is validated on a 3-kW permanent magnet synchronous motor driven by a two-level inverter, and the experimental results are consistent with theoretical analysis.

The performance of low-voltage circuit breaker overload protection degrades slowly during service, and the service state cannot be simply described as a normal state or a fault state. To address this problem, a method is proposed to classify the operating state of low-voltage circuit breaker overload protection, taking into account the safety margin of action characteristics and a Markov-process-based operating state transfer model is established to accurately describe its actual service state. By analyzing the degradation of the overload protection performance of circuit breakers and simulating the state transfer with different operating conditions using circuit breaker reliability levels and operating time as the main variables, the change law of the service state with service time is determined. The method is not only applicable to the analysis and evaluation of circuit breakers with different reliability levels but also has guiding significance for improving the safe operation of distribution grid systems.

Residual current circuit breakers are important terminal protection apparatus in low-voltage distribution systems, which play a major role in preventing leakage accidents and protecting the personal safety of power users. The leakage protection module is composed of electronic components, and its parameter deviation and degradation cause parameter drift, which will cause the protection performance degradation of residual current circuit breaker. Therefore, the simulation model of leakage protection module is established, and sensitivity analysis is adopted to identify the key components of leakage protection module. Considering the performance difference caused by tolerance, the Monte-Carlo simulation is used to obtain system performance degradation data. The leakage protection module degradation caused by the degradation of components is analyzed, and the reliability evaluation of leakage protection is realized according to the performance change, which can provide decision support for early design.

交流接触器广泛用于电力系统,精准评估其可靠性是保障系统安全平稳运行的关键.现有交流接触器可靠性研究没有考虑三相触头的竞争失效、退化相关性,及各相触头失效阈值均有随机性等问题,可能造成可靠性评估不精准.针对这些问题,本文用累积电弧侵蚀量表征性能状态,建立了考虑竞争失效、退化相关性和失效阈值随机性的退化模型;对模型参数较多且难以同时估计所有参数的问题,提出了基于极大似然估计的多阶段参数估计方法;基于蒙特卡洛技术提出了可靠度近似计算方法,并基于黎曼和技术推导出平均故障时间的近似式;最后,通过仿真与实例分析验证了所提方法的有效性.实例分析表明所提可靠性评估方法精度较高,其拟合优度比现有方法提升了约 45％.