Variational Mode Decomposition-Informed Empirical Wavelet Transform for Electric Vibrator Noise Analysis

Electric vibrators find wide applications in reliability testing, waveform generation, and vibration simulation, making their noise characteristics a topic of significant interest. While Variational Mode Decomposition (VMD) and Empirical Wavelet Transform (EWT) offer valuable support for studying signal components, they also present certain limitations. This article integrates the strengths of both methods and proposes an enhanced approach that integrates VMD into the frequency band division principle of EWT. Initially, the method decomposes the signal using VMD, determining the mode count based on residuals, and subsequently employs EWT decomposition based on this information. This addresses mode aliasing issues in the original method while capitalizing on VMD’s adaptability. Feasibility was confirmed through simulation signals and ultimately applied to noise signals from vibrators. Experimental results demonstrate that the improved method not only resolves EWT frequency band division challenges but also effectively decomposes signal components compared to the VMD method.

基于Transformer的纯电动汽车充电时间预测

纯电动汽车充电时间的安排是车主日常生活中至关重要的环节,直接影响车主出行的便利度和舒适体验。然而,目前仍然面临充电桩资源不足、充电须提前规划等挑战,为解决车主因车辆电量不足而无法立即用车的问题,提出一种基于Transformer模型的充电时间预测解决方案,帮助车主更好地规划日常行程。为了更好地了解电池性能衰减程度和容量损失情况,采用容量法评估电池健康状态,并分析驾驶人的充电行为,对电池充电行为特征进行构建。使用Savitzky-Golay滤波器对表征电池衰减的特征进行平滑处理,并进行累积变换,使特征能更全面地表征电池信息;再耦合皮尔逊相关系数和LASSO(least absolute shrinkage and selection operator)回归算法二次筛选得到最优特征集。最后,利用Transformer模型的超强注意力机制,对充电时间进行预测。通过实验数据验证,此方案可以准确且快速地预测纯电动汽车的充电时间,决定系数达到0.999,运行时间为156 ms。

基于变量选择与Transformer模型的中长期电力负荷预测方法

准确且有效的负荷预测对于电力系统的实时运行和调度非常重要。提出了一种融合变量选择与稀疏Transformer模型的预测方法,将静态变量和时序变量作为输入,充分发挥静态变量在全局时间范围内的信息增强作用,基于门控机制设计变量分权组件,根据变量与预测结果的相关性,赋予变量不同的权重。设计了双层编码结构,进行时序特征提取,对注意力进行稀疏处理,通过多变量输入对未来时刻负荷进行预测。基于真实电力负荷数据的实验表明,本文模型能够提高中长期负荷预测精度和效率。

基于改进Transformer的变电站复杂场景下电力设备分割

【目的】变电站电力设备种类多设备之间连接关系复杂,普遍存在设备位置和图像对比较为单一,实际应用中只能获得有限数量的目标图像和标记以及传统方式分割带来的电力设备图像分割精度不够的问题,将卷积神经网络(Convolution Neural Network,CNN)与Transformmer结合组成新模型进行变电站电力设备的分割,提出了一种基于编解码器结构的新型SE-Transfomer(Substation Equipment Transformer)网络。【方法】为了获取局部上下文信息,编码器首先利用CNN提取空间特征图。同时,对特征图进行了精心改造,多尺度特征输入进行全局特征建模。该解码器利用Transformer提取全局深层特征,并进行逐步上采样来预测详细的分割图。SE-Transfomer在山西省梁家庄变电站数据集上进行广泛实验,其纵向结果的Dice系数(Dice)、召回率(Recall)、特异度(Specificity)和均方根误差(RMSE)分别为89.31%,90.52%,89.62%和11.32.【结果】结果表明,SE-Transfomer在变电站电力设备的扫描上获得了与以往最先进的分割方法相当或更高的结果。

Swin-Transformer故障信息挖掘的海底观测网故障定位方法

海底观测网长期受海洋环境与人为因素影响,易使光电复合缆绝缘破损与海水接触形成电学故障点。如何准确地定位电学故障点,对提高海底观测网输电与信息传输的可靠性至关重要。首先根据海底观测网输电结构建立海底观测网输电模型,推导与模拟电学故障点传播至观测点的暂态电流,然后由连续小波变换提取暂态电流与故障点对应的内在关联特征量,最后通过Swin-Transformer神经网络挖掘内在关联特征量与故障距离的匹配关系来定位电学故障点。研究结果表明,在内在关联特征量样本测试集条件下,光电复合缆≤160 km的电学故障点定位误差小于400 m,可为长距离光电复合缆的海底观测网电学故障点定位提供参考。

考虑多维影响因素的改进Transformer-PSO短期电价预测方法

随着多元化电力市场的建设,电价影响因素日益增加,市场环境变化也更加剧烈.为提高市场短期电价的预测精度,提出一种考虑多种电价影响因素的改进Transformer-粒子群优化(PSO)算法短期电价预测方法.首先,在考虑历史电价、负荷的基础上进一步分析电价形成的相关因素,利用自相关函数分析电价的多周期特性并在此基础上调整输入序列,克服了仅采用历史数据以及经验调整输入序列导致预测精度受限的问题.其次,结合长短期记忆(LSTM)、自注意力机制与多层注意力机制并采用多输入结构建立改进Transformer模型,进一步提升LSTM模型捕获不同时间步信息间的长短期依赖关系的能力,克服LSTM的信息利用瓶颈,适应包括历史电价及多种电价成因的复杂多序列输入.此外,还利用PSO智能算法搜索模型不同学习阶段的最佳学习率克服手动调整学习率的局限性.最后,采用PJM市场电价进行算例分析,结果表明所提短期电价预测模型能应用于电价影响因素多、变化剧烈的市场环境,并有效提升短期电价预测精度.

基于强化学习和Transformer的输电线路缺陷智能检测方法研究

为了解决传统输电线路缺陷检测方法的不足,该文提出了一种基于强化学习和Transformer的输电线路缺陷智能识别方法。首先,采用具有较大感受野的空洞卷积网络(deterministic networking, DetNet)对输电线路巡检缺陷图像进行特征提取,继而使用深度Q网络(deepQ-network,DQN)筛选出包含前景信息的重要区域。其次,基于双线性注意力机制对背景区域特征向量进行投影压缩,使得融合特征向量聚焦于目标区域。最后,针对不确定缺陷检测结果定义可信度评测指标,构建Transformer网络编码层级的自适应调整机制,建立具有不同编码层级的Transformer模型库,以获取多模态缺陷的多层次差异化特征,采用Soft-NMS获取集成检测结果,提升识别模型的鲁棒性。通过对输电线路缺陷航拍图像进行了实验研究,该文方法检测精度平均值为89.7%,与其他算法相比具有更优的检测精度和泛化能力。

General Nexus Between Water and Electricity Use and Its Implication for Urban Agricultural Sustainability:A Case Study of Shenzhen, South China

Although water and energy resources are well-recognized concerns regarding economic and social development sustainability, little specific research has focused on both water and energy problems at the same time. This study analyzed the water and electricity-use patterns in Shenzhen, South China during 2001-2009. A curve regression method was used to examine the relationship between water and electricity use per gross domestic product （GDP） in Shenzhen and its three sectors, i.e., agriculture, industry ＆ construction, and residential life ＆ services. Results showed that agriculture only covered less than 10% of water and electricity use in Shenzhen, while industry ＆ construction and residential life ＆ services accounted for more than 90% of water and electricity use in Shenzhen, which coincided with the city＇s industrial structure. The water and electricity use per GDP in agriculture was the biggest among three sectors in Shenzhen during 2001-2009, which means inefficiency of water and electricity use in agriculture. Due to transitioning to advanced materials and manufacturing, both water and electricity use per GDP their utilization efficiencies gradually increased over time. in industry ＆ construction decreased during 2001-2009 and The same held true for those in residential life ＆ services transformed toward modern business, creative culture, finance services, etc. Derived from the survival of the fittest in competing for limited water and electricity resources, agriculture in Shenzhen has been gradually substituted by industry ＆ construction and residential life ＆ services, with much higher efficiencies of water and electricity use. And traditional agriculture will not be sustainable in the process of urbanization and industrialization, except high-tech intensive agriculture with low water and energy cost. Furthermore, by means of curve regression, we found that there was a significant quadratic relationship between water use per GDP and electricity use per GDP in the entire city and its three sectors. Suitable industrial transformation and advancement was a very effective way to save water and energy for modern cities. This can provide some reference for systematic planning and design of water and electricity allocation and use in agriculture, industry ＆ construction and residential life ＆ services in a city.

Modeling electric field of power metal-oxide-semiconductor field-effect transistor with dielectric trench based on Schwarz–Christoffel transformation

A power metal-oxide-semiconductor field-effect transistor(MOSFET) with dielectric trench is investigated to enhance the reversed blocking capability. The dielectric trench with a low permittivity to reduce the electric field at reversed blocking state has been studied. To analyze the electric field, the drift region is segmented into four regions, where the conformal mapping method based on Schwarz–Christoffel transformation has been applied. According to the analysis, the improvement in the electric field for using the low permittivity trench is mainly due to the two electric field peaks generated in the drift region around this dielectric trench. The analytical results of the electric field and the potential models are in good agreement with the simulation results.

Analysis of Non-Sinusoidal Steady Electric Field of ±500 kV Converter Transformer

The line side winding is under the fundamental frequency AC voltage, while the valve side winding contains not only fundamental AC voltage component, but also the DC voltage component, fundamental AC voltage component, and higher harmonic voltage components when the converter transformer is at its normal operating condition, and the electric field of converter transformer is a non-sinusoidal steady one. To analyze the non-sinusoidal steady electric field containing the DC component, fundamental AC and higher harmonic components, the voltage spectrum of the valve winding in a ±500 kV converter transformer is firstly analyzed, and the non-sinusoidal periodic steady electric field is obtained by the fast discrete Fourier transform. Different resistivity of the oil and oil-immersed paper is adopted to simulate the aging of oil paper insulation at operation, and get the non-sinusoidal steady electric field.

Insulation System of Power Transformers Behavior Comparison of Mineral Oils and Natural Ester Dielectric Fluids

Paper deals with a comparison of selected properties of several vegetable oil representatives along their accelerated thermal ageing at the temperature of 90 ℃. These properties are compared to two widely used and commercially available mineral transformer oils. A combined insulating system （an oil-paper system） was created with the usage of mentioned oils for measurement purposes. Dissipation factor, capacity and volume resistance are characteristics measured along a thermal ageing of the oil-paper systems. Infrared spectroscopy was used as an additional method. After 1,000 hours of ageing, the dissipation factor of all systems based on vegetable oils did not exceed the value of 0.015. The volume resistance of systems containing mineral oils was approx, twice as high as the volume resistance of those with vegetable oils. The capacity on the other hand was slightly lower in the case of mineral oils application. An experiment also showed that the paper combined with the vegetable oil dries more quickly than in combination with the mineral oil. Infrared spectroscopy has not shown any expressive changes in the chemical structure of aU tested oils yet （up to 1,000 hours of ageing）.

Model Transformer Evaluation of High-Permeability Grain-Oriented Electrical Steels

The dependence of transformer performance on the material properties was investigated using two laboratory-processed 0.23 mm thick grain-oriented electrical steels domain-refined with elec-trolytically etched grooves having different magnetic properties. The iron loss at 1.7 T, 50 Hz and the flux density at 800 A/m of material A were 0.73 W/kg and 1.89 T, respectively; and those of material B, 0.83 W/kg and 1.88 T. Model stacked and wound transformer core experiments using the tested materials exhibited performance well reflecting the material characteristics. In a three-phase stacked core with step-lap joints excited to 1.7 T, 50 Hz, the core loss, the exciting current and the noise level were 0.86 W/kg, 0.74 A and 52 dB, respectively, with material A; and 0.97 W/kg, 1.0 A and 54 dB with material B. The building factors for the core losses of the two materials were almost the same in both core configurations. The effect of higher harmonics on transformer performance was also investigated.

The c-axis complex permittivity and electrical impedance in BaFe_2As_2: Experimental examination on transformation validity

Complex permittivity and electrical impedance have been measured along the c-axis in single crystals BaFe_2 As_2,which are the conductors known as the parent compound of 122-type iron superconductor. The resultant relative errors defined in the study indicate the existence of the transformation between complex permittivity and electrical impedance in the conductors, and these two physics quantities possibly reveal different aspects of the consistent superconductivityrelevant physics picture.

Low-loss B18R065 and B20R070 grain oriented electrical steels for grade 1 energy efficiency distribution transformers

To reduce distribution transformer losses and carbon dioxide emissions, in recent years, the major countries in the world have issued mandatory standards for high-energy efficiency in distribution transformers. In 2013,China has carried out a new standard GB 20052-2013. To meet the update of the standard and energy efficiency,it is important to enhance the magnetic properties of core materials. The new products B18R065 and B20R070 which are developed by Baosteel, are successfully used for grade 1 energy efficiency distribution transformers. And Baosteel becomes one of the companies which can supply both the 0.20 mm and the 0.18 mm gauge grain oriented electrical steels （GOES） in the world. The development principle, material properties, and transformer performance of B18R065 and B20R070 were introduced,which were expected to be a useful reference for materials selection by transformer manufacturers.

Management of Charging Load of Electric Vehicles for Optimal Capacity Utilisation of Distribution Transformers

A de-centralised load management technique exploiting the flexibility in the charging of Electric Vehicles (EVs) is presented. Two charging regimes are assumed. The Controlled Charging Regime (CCR) between 16:30 hours and 06:00 hours of the next day and the Uncontrolled Charging Regime (UCR) between 06:00 hours and 16:30 hours of the same day. During the CCR, the charging of EVs is coordinated and controlled by means of a wireless two-way communication link between EV Smart Charge Controllers (EVSCCs) at EV owners’ premises and the EV Load Controller (EVLC) at the local LV distribution substation. The EVLC sorts the EVs batteries in ascending order of their states of charge (SoC) and sends command signals for charging to as many EVs as the transformer could allow at that interval based on the condition of the transformer as analysed by the Distribution Transformer Monitor (DTM). A real and typical urban LV area distribution network in Great Britain (GB) is used as the case study. The technique is applied on the LV area when its transformer is carrying the future load demand of the area on a typical winter weekday in the year 2050. To achieve the load management, load demand of the LV area network is decomposed into Non-EV load and EV load. The load on the transformer is managed by varying the EV load in an optimisation objective function which maximises the capacity utilisation of the transformer subject to operational constraints and non-disruption of daily trips of EV owners. Results show that with the proposed load management technique, LV distribution networks could accommodate high uptake of EVs without compromising the useful normal life expectancy of distribution transformers before the need for capacity reinforcement.

基于Transformer网络和多任务学习的园区综合能源系统电-热短期负荷预测方法

负荷预测是综合能源系统(integrated energy system,IES)能量管理和优化调度的基础,其预测精度直接关系到系统的整体运行性能。提出了一种基于Transformer网络和多任务学习的园区综合能源系统电-热短期负荷预测模型。首先对Transformer网络和多任务学习结构的基本原理进行了介绍;然后通过基于随机森林的特征选择步骤提取反映负荷特性和变化规律的典型指标,构建多任务学习输入特征,基于Transformer网络构建多任务学习权值共享层,并通过全连接层输出多能负荷的预测值;最后通过实际园区微能源系统的数据验证所提方法和算法的有效性,结果表明本文所提模型可以充分学习电-热耦合特征,提高负荷预测的精度。

Analysis of Necessity of Transforming Electrical Grid Access Training and Examination Regulatory Agency Mode

There are numerous electricians,but only a few of them have obtained certificate. Training and examination agencies provide services relating to training,examination,and certificate application and so on.Thus,training resources are not rationally utilized,and the increased training demand cannot be fully satisfied.Under such circumstances,it is recommended to transform the regulatory agency mode by establishing a scientific management process,and put forward a new mode of electrical grid access training and examination to better meet related demands. Under the coordination of examination center regulatory agency, uniform training program,training materials,charging standard,examination and certificate can be guaranteed. This project is carried out as an effort to improve the quality of electronic- engineering training and examination,so that electricity accident rate can be reduced,and the security of electrical grid operation can be guaranteed to boost the rapidly developing economy.

基于Transformer算法的园区综合能源需求预测

准确的综合能源需求预测是区域综合能源系统调度和能效评估的基础。在综合能源需求预测方面,影响因素众多、设计参数复杂、计算效率较低,且在长序列预测上仍有较大优化空间,因此提出了一种基于Transformer算法的园区综合能源需求预测方法。建立了园区冷热电负荷影响因素的筛选模型,为数据预处理后筛选适当的影响因素提供基础;建立了基于欧氏距离的综合相似度的相似日选取方法,为综合能源的预测奠定了基础;建立了基于Transformer算法的冷热电负荷预测模型,以实现园区综合能源需求预测;以中国东部某园区为对象进行算例分析,预测园区综合能源需求。结果表明,所提预测方法能有效提高预测精度,具有较高的准确度和实用性。

“电机学”课程虚拟仿真实验建设

电机学实验是工程基础课程“电机学”必要环节。针对理论教学中存在概念难理解、现象直观性差,实物实验内容全面性不足的问题,将有限元虚拟仿真技术应用于实验教学中,直观展示电机的运行机理和电磁特性,解决教学难题。在阐述虚拟仿真实验建设思路的基础上,以变压器仿真实验建设为例说明虚拟仿真实验设计方法和开展过程。教学实践证明,在电机实验教学中开展虚拟仿真实验,保证了实验内容的全面性和系统性,学生的工程实践能力和创新意识得到提高。

基于正弦同源-概率空间协同互补的涌流闭锁方案

为了取消正弦相似性原理中的最小二乘法等中间环节,获得直接固定标准正弦波形所需要的能量信息。借鉴时域概率分布的方法论,从优势互补的角度出发,设计了一种基于Wasserstein距离算法的变压器励磁涌流闭锁方案。该方案采用特征离散化的方式,提取目标对象和模板信号并转化为状态向量作为样本标签,以此来判别两者之间的能量分布差异,从而达到正弦场景同源识别的效果。理论分析与仿真结果表明,该方法实现简便,不需要频域计算。相比于现有正弦相似性原理,降低了保护流程的复杂程度,具有更强的实际应用价值和速动性能。通过PSCAD/MATLAB平台对现场合闸的录波数据进行测试分析,验证了所提方案对促进变压器保护性能的积极意义。