Experimental and analytical studies on multiple tuned mass dampers for seismic protection of porcelain electrical equipment

Porcelain electrical equipment （PEE）, such as current transformers, is critical to power supply systems, but its seismic performance during past earthquakes has not been satisfactory. This paper studies the seismic performance of two typical types of PEE and proposes a damping method for PEE based on multiple tuned mass dampers （MTMD）. An MTMD damping device involving three mass units, named a triple tuned mass damper （TTMD）, is designed and manufactured. Through shake table tests and finite element analysis, the dynamic characteristics of the PEE are studied and the effectiveness of the MTMD damping method is verified. The adverse influence of MTMD redundant mass to damping efficiency is studied and relevant equations are derived. MTMD robustness is verified through adjusting TTMD control frequencies. The damping effectiveness of TTMD, when the peak ground acceleration far exceeds the design value, is studied. Both shake table tests and finite element analysis indicate that MTMD is effective and robust in attenuating PEE seismic responses. TTMD remains effective when the PGA far exceeds the design value and when control deviations are considered.

A Comparison of Domestic and Foreign Seismic Fortification Standards for Electrical Equipment

It is of great significance to make comparative analyses of seismic fortification criteria at home and abroad for improving the anti-seismic capability of electrical equipment and revising the relevant national standards.A brief overview of American,Japanese,IEC standards and Chinese seismic design codes for electrical equipment is presented.Differences between these seismic fortification standards of electrical equipment are compared and analyzed in respect of the goal and level of seismic fortification and the seismic design spectrum.The advantages and disadvantages of Chinese standards are pointed out.Through learning from foreign experience on the determination of seismic fortification standards,recommendations are made for the improvement and revision of Chinese seismic fortification standards for electrical equipment.

基于YOLOv5s和Android部署的电气设备识别

针对变电站多种电气设备实时检测的需求,提出了一种基于改进YOLOv5s的电气设备识别方法,并设计基于Android部署的电气设备识别APP,以便对电气设备进行识别与学习。以电力变压器、绝缘子串等6种常见变电站电气设备为例构建图像数据集。数据集进行图像预处理后对YOLOv5s算法进行改进。通过引入C2f模块提高小目标检测精度,采用Soft-NMS提高检测框筛选能力,减少漏检和误检的情况,使用改进后的算法对数据集进行模型训练。将训练好的识别网络模型通过TensorFlow Lite框架进行模型部署,设计电气设备识别APP。经验证,改进后的变电站电气设备识别网络模型mAP稳定在91.6%,与原模型相比提高了3.3百分点。部署后的APP具有设备识别和设备介绍等界面,使用移动端进行识别时每张图片识别时间都小于1 s,具有较快的识别速度和较高的识别精度,可以高效地实现变电站电气设备的实时检测与设备学习。

New “Intellectual Networks” (Smart Grid) for Detecting Electrical Equipment Faults, Defects and Weaknesses

The most important elements of “intellectual networks” (Smart Grid) are the systems of monitoring the parameters of electrical equipment. Information-measuring systems (IMS), which described in this paper, were proposed to use together with rapid digital protection against short-circuit regimes in transformer windings. This paper presents an application’s experience of LVI-testing, some results of the use of Frequency Response Analysis (FRA) to check the condition of transformer windings and infra-red control results of electrical equipment. The LVI method and short-circuit inductive reactance measurements are sensitive for detecting such faults as radial, axial winding deformations, a twisting of low-voltage or regulating winding, a losing of winding’s pressing and others.

Characteristic Period Value of the Seismic Design Response Spectrum of UHV Electrical Equipment

Characteristic period is an important parameter of the seismic design response spectrum. There is important theoretical significance and engineering application value to the study of the characteristic period of seismic design response spectrum of ultra high voltage （UHV） electrical equipment. In this paper, 1448 horizontal earthquake records within the world scope including the United States and Japan for Site Class m were analyzed. Results show that both magnitude and epicentral distance have great influence on the characteristic period. About 80 % of characteristic periods of strong earthquake records are about 0. 9s. Statistical analysis was conducted on the seismic hazard assessment results of 312 projects of China in recent years, and it is found that about 70 % of characteristic periods are about 0. 9s. Combined with the related code comparison and analysis, it is suggested that the characteristic period of the seismic design response spectrmn of UHV electrical equipment should select 0. 9s in order to effectively guarantee the seismic safety of UHV electrical equipment.

Simplified Modeling and Mathematical Analysis in Cardiac Electric Field Propagation for Human and Animals

The different characteristics of cardiac electric field(CEF)radiation in humans and other animals are presented in this paper.Physical modeling and mathematical analysis are developed to comprehensively unveil the properties of CEF,based on typical heartbeat waveforms.Our numerical simulation results demonstrate that the frequency bandwidths and the cycle durations of CEF are different for healthy humans versus humans on the verge of death and for humans versus other animals.The results indicate that the present study may extensively contribute towards recognizing human beings or other animal targets quickly and accurately with CEF in dangerous situations or in other applications.

Importance of Life Cycle Analysis of the Printed Circuit Board Computer

It is estimated that there is a generation of 307,224 ton/year [1] of waste from electronic and electronic equipment (WEEE) in Mexico, of which 10% is recycled, 40% remains stored and 50% reaches landfills or uncontrolled dumps. In the practice, even the regulatory instruments are not consolidated and the adequate management of the use of WEEE management, so the aim of this study is an analysis of life cycle of printed circuit boards (TCI) to identify the management alternatives that represent the least impact to the environment. This assessment was carried out using software SIMAPRO to determine the environmental impact of each scenario, through the comparison of impacts and the proposed improvements to reduce it, following phases of this methodology by applying standards, ISO 14040/ISO 14044 [2], using data from the INE official reports since 2006 until 2010 which concentrate the information of the WEEE problem in Mexico. These data were pooled to carry out inventories according to the availability in the information, identifying the environmental impacts generated by processing. The conclusions of the LCA will serve to identify the stage with greater environmental impact, and thus propose ideas for improvement in order to minimize this impact.

基于电学参数的贺兰山东麓赤霞珠葡萄酒子产区判别

本研究以宁夏贺兰山东麓5个子产区(银川、青铜峡、红寺堡、石嘴山和农垦产区)自然发酵的赤霞珠干红葡萄酒为研究对象,测定其基本理化指标和电学特性,分析不同产区葡萄酒间电学特性的差异,筛选出区分不同产区葡萄酒的特征频率和有效电学参数,初步探索基于电学特性识别宁夏贺兰山东麓不同子产区葡萄酒的能力,以期为简捷快速有效识别产区葡萄酒提供新方法。结果表明,宁夏贺兰山东麓5个子产区的葡萄酒理化指标间存在显著性差异,农垦产区的葡萄酒可滴定酸含量最高,而还原糖含量最低;银川产区的葡萄酒挥发酸含量最低,石嘴山产区的葡萄酒酒精度最高。通过相关性分析、方差分析和多重比较,筛选出电压2 V下,区分不同产区葡萄酒的电学特性特征频率为0.1 kHz,有效电学参数为Z、L_(p)、X、C_(p)和Q。主成分分析和判别分析均显示,利用葡萄酒电学参数能够明显区分贺兰山东麓5个子产区,采用Fisher-判别分析建立的预测模型,其回代检测和交叉验证正确率均为100%。因此,利用葡萄酒电学特性识别产区具有可行性。

CEEMD-FastICA-CWT联合瞬态响应阶次的电驱总成噪声源识别

以某增程式电驱动总成为研究对象,提出基于联合算法的噪声分离识别模型。首先,采用互补集合经验模态分解(complementary ensemble empirical mode decomposition,CEEMD)联合快速独立分量分析(fast independent component analysis,FastICA)方法提取纯电模式稳态工况下单一通道噪声信号特征,利用复Morlet小波变换及FFT对各分量信号时频特性进行识别。其次,采用阶次分析法和声能叠加法对稳态分量信号对应的各瞬态响应阶次能量进行对比分析,并结合皮尔逊积矩相关系数(Pearson product moment correlation coefficient,PPMCC)相似性识别确定不同噪声激励源贡献度。结果表明:减速齿副啮合噪声对该增程式电驱总成纯电模式运行噪声整体贡献度最大。

电力系统中的雷电暂态感知、监测和应用

雷电是造成电力系统故障的首要原因,实现对雷电暂态电压电流信号的感知、监测和数据应用对于维护系统安全稳定运行具有重要意义。面向日益复杂的新型电力系统结构形态,传感器件在满足雷电宽频测量的基础上,监测装置正朝着微型化、高精度、强互联和易取能方向发展。因此,该文基于雷电暂态感知方法、监测装置关键技术和雷击数据统计应用的研究现状,首先介绍了基于不同原理的电压/电场和电流/磁场传感技术,并分析了各自的优缺点;其次梳理了传感器微型化、时间同步、通信和供能等关键技术的最新进展;随后通过对雷击暂态波形的统计分析,探讨了监测数据在雷击故障识别与定位中的应用;最后对电力系统中雷电暂态感知、监测与应用进行总结并对其发展趋势作出展望。

纯电动汽车用异步电机损耗最小控制策略研究

为提升电动汽车续航里程,研究加入铁损电阻参数辨识的节能降耗控制策略。基于异步电机工作机理,分析异步电机不同性质下的损耗,对损耗电阻进行在线辨识,建立考虑铁损的电路模型,推导出基于在线辨识和计及铁损的异步电机损耗最小控制电流,实现了节能控制,并搭建系统仿真模型和测试实验平台,开展车用异步电机多工况下的仿真实验和性能测试实验。实验结果表明,所研究的策略能较好地辨识铁损电阻,能有效提升异步电机的效率,提高一次充电续航能力,该策略在工程应用上具有一定的实用价值。

基于改进单阶段目标检测算法的换流站电气设备目标检测

针对换流站多种电气设备检测时背景复杂干扰性强而又需要快速准确检测出故障的实际情况,提出基于改进YOLOv5(You Only Look Once)的检测方法。首先,为提高算法的准确性和收敛速度,通过K-means聚类算法对YOLOv5模型中的锚框预设进行改进,在数据集预处理阶段得到更适用于换流站电气设备的锚框,使其更加契合换流站电力设备数据集;然后,为提高算法检测过程的识别速度,在特征提取网络添加注意力机制模块,筛选出重要的特征信息。将改进后的算法网络识别效果与YOLOv5中的原始算法网络检测结果进行对比分析。结果表明,检测平均识别精度均值由71.16%提高至92.51%,检测速度由21帧/s提升至31帧/s;同时与R-CNN(Regions with convolutional neural networks)等算法相比,检测精度与速度都有较大提升。添加可解释性分析,将识别结果通过热力图的形式显示,可以更好地应对算法的潜在风险。

基于先验统计模型的非侵入负荷辨识算法

针对传统非侵入负荷辨识技术中电热细分能力不足的问题,文中提出了一种基于先验知识与统计学习模型的居民非侵入式负荷辨识算法。文中对洗衣机辅热、电水壶、电饭锅、电热水器等设备进行了电热细分研究,通过设备运行关联算法实现了辅热设备的细分,并在用户有限反馈信息和专家标注的基础上,实现了非辅热设备分类的模型训练。实验结果表明,文中所提技术框架在事件检测负荷辨识算法的基础上实现了电热设备的细分,且在运行状态分解的F1分数指标中取得了0.9以上的优异效果。

EDS成分分析法在电气熔痕鉴定中的应用

EDS成分分析法是微量物证鉴定的常用方法,具有灵敏度高、操作简单快速等特点,在纤维、金属、玻璃、油漆及纸张等各类微量物证的鉴定中有着广泛的应用。在火灾痕迹物证鉴定领域,EDS成分分析法已成为重要方法之一。通过探讨三起采用EDS成分分析法对电气熔痕进行鉴定的实例,提出在火灾现场物证取样、熔痕鉴定和鉴定意见运用等方面的注意事项。

高速公路机电设备健康状态物联监测与智能诊断

针对高速公路机电设备运维管理存在健康状态数据不能实时获取、故障发现不够及时准确、设备维护处理效率较低等问题,本文提出应用物联网和智能诊断模型处理技术,构建一种远程机电设备健康状态物联监测与智能诊断系统。该系统通过实时监测设备基础状态数据,利用物联网技术将数据传输到云处理平台,对数据进行分析、处理、判断机电设备运行的健康状态及故障智能诊断。实际运行结果表明:该系统可准确地判断外场机电设备的健康状态,减少现场维护频次约15%,缩短运维和巡检车辆行驶里程约30%,实现了节能减排,降低了运维成本,缓解了高速公路拥堵,进而取得良好的经济和社会效益。

医院周期性电工倒闸对医疗设备的危害分析及应对策略

目的:制定医疗设备配电安全目标与应对策略,最大程度降低电工倒闸对医疗设备的危害。方法:基于危害分析与风险评估(HARA)方法,从医疗设备安全管理角度对2018-2023年北京儿童医院的电工倒闸进行医疗设备危害因素分析与风险评估,采用戴明循环(PDCA)管理法的闭环管理流程,制定精细化的医疗设备配电安全目标与应对策略。结果:2023年医院配电室开展的2次周期性电工倒闸操作共发生6台次设备故障问题,显著低于2018-2022年电工倒闸导致的20.4台次故障平均值,且一级负荷科室等高风险级区域故障为零。结论:制定的医疗设备配电安全目标与应对策略针对性强、执行度高,是实施医疗设备全生命周期精细化管理的有效方法。

基于多突变点与模板匹配的用电设备在线状态监测方法

针对现阶段用电设备状态监测技术存在的处理速度较慢、准确率较低等问题,文中基于多突变点检测和模板匹配策略提出了一种用电设备在线状态监测方法。该方法在缓冲区模型和滑动窗口模型的基础上,利用多路搜索树突变点检测(Ternary Search Tree and Kolmogorov-Smirnov,TSTKS)算法形成窗口维度和缓冲区维度的特征向量,通过两种维度的模板匹配实现用电设备的运行状态匹配和状态切换时刻定位。基于家用电冰箱的仿真实验结果表明,所提方法具有检测速度快、准确率高等优点,可为用电设备状态监测领域提供参考。

复合支柱绝缘子在长期载荷下的损伤识别方法

复合材料在电气设备中的应用越来越广泛,其具有损伤隐蔽性的特点。复合材料设备受到长期环境荷载的作用之后,结构会累积不同程度的微小损伤且不易被发现。为了研究复合电气设备的损伤识别方法,以某200 kV复合支柱绝缘子为研究对象,首先分别进行不同损伤工况下的现场动力特性测试,得出不同工况下的频率变化;其次进行数值模拟,通过曲率模态差值分析和小波变换2种方法对绝缘子进行损伤识别;最后以曲率模态差为损伤指标得到该绝缘子的损伤曲线。研究表明:2种识别方法都可以有效地对绝缘子损伤位置进行识别,且小波变换的方法更为优越;损伤曲线可以通过曲率模态差较为准确地拟合损伤程度的大小。

一种用电设备分析识别原理与应用

非侵入式负荷监测(NILM)与识别是智能电网建设的重要方面。针对非侵入式用电负荷监测技术提出了一种基于V-I轨迹与奇次谐波分量特征的混合特征矩阵和卷积神经网络相结合的方法。具体内容为:分析用电设备的基本特征,包括输入电流稳态特征和暂态特征。建立了六种单相交流电源供电的用电设备MATLAB/Simulink仿真电路,分别为电阻加热器、电吹风、LED灯串、电源适配器、变频空调和变频冰箱,作为待分析识别的用电设备,并提取了这六种负荷模型的网侧电流波形和频谱、V-I轨迹以及奇次谐波电流分量数据作为基本特征量;提出了一种采用V-I轨迹与奇次谐波特征的混合特征矩阵以及卷积神经网络(CNN)进行用电设备分析识别,经过PLAID数据集的训练和测试,能够有效识别稳态运行下的用电设备,给出了详细的解算过程,并提供了应用算例。此外,对比分析了已有三种检测方法,验证本文提出的基于混合特征矩阵以及卷积神经网络用电设备分析识别方法的优越性。

基于机器学习算法的电气设备故障智能检测技术研究

随着智能制造和工业自动化的不断推进,电气设备的稳定运行变得日益重要。然而,故障的不可预测性给设备维护带来了巨大挑战。因此,本文提出了一种基于主成分分析的电气设备故障智能检测技术,以提高故障诊断的准确性和效率。首先,分析了电气设备故障的常见类型和特征,以及影响故障检测准确性的关键因素。其次,提出一种基于主成分分析的电气设备故障智能检测技术,通过在线学习机制,使模型能够适应新的故障特征,实现持续优化和迭代更新。最后,为了验证所提出方法的有效性,研究构建了一个基于实际电气设备数据的测试平台。结果表明,所提出的故障智能检测方法能够有效识别复杂故障模式,并实现了对早期故障迹象的准确预警。