高温超导电缆终端预制式应力锥的设计与分析北大核心

高温超导电缆终端是高温超导电缆系统的重要组成部分。借鉴常规电缆终端预制式应力锥的设计理论,结合高温超导带材的特殊工作特性,选用耐低温的绝缘材料,对高温超导电缆终端预制式应力锥进行设计。运用有限元分析软件ANSYS对设计的高温超导电缆终端预制式应力锥进行建模和仿真计算,得到终端处的电场和电位分布,并将仿真结果和理论计算结果进行对比分析,验证设计的可行性,为进一步的研究奠定了基础。     

高温超导电缆终端预制式应力锥的设计与分析

高温超导电缆终端是高温超导电缆系统的重要组成部分。借鉴常规电缆终端预制式应力锥的设计理论,结合高温超导带材的特殊工作特性,选用耐低温的绝缘材料,对高温超导电缆终端预制式应力锥进行设计。运用有限元分析软件ANSYS对设计的高温超导电缆终端预制式应力锥进行建模和仿真计算,得到终端处的电场和电位分布,并将仿真结果和理论计算结果进行对比分析,验证设计的可行性,为进一步的研究奠定了基础。     

高温超导电缆终端预制式应力锥缺陷的研究分析

高温超导电缆终端是连接超导电缆和常规电缆的重要组成部分。其中应力锥作为改善电场分布的终端元件之一,具有无可替代的功用。但应力锥在生产过程中,不可避免的会产生一些缺陷,导致电缆终端电场集中,产生放电或烧毁电缆。文中针对高温超导电缆终端应力锥可能出现的各种缺陷进行建模与分析,运用有限元分析软件ANSYS对其进行仿真,得到电缆终端的电场和电位分布。为进一步研究应力锥的设计奠定基础。     

高温超导电缆电磁结构的优化设计

高温超导电缆层间电流分布不均是超导电缆研究的重要问题之一,调整电磁结构是使其各层电流分布趋于均衡的有效途径。文中建立了电缆本体的电路矩阵方程,分析了导电层电流及其产生的磁场,推导了各导电层自感和层间互感的计算公式。在此基础上,给出了以电缆各层电流均衡为目标的优化函数,并用该函数对超导电缆实例进行了结构优化。仿真结果表明,优化后电缆的各层电流分布趋于均衡。     

100kV直流高温超导电缆终端应力锥设计

本文提出了一种新的单直线应力锥设计方法,根据PPLP材料的绝缘特性,结合超导电缆的本体尺寸和设计电压,给出了增饶绝缘厚度和应力锥轴向长度的设计数据,其中增饶绝缘厚度为3.5 mm,应力锥轴向长度为38.5 mm,并对单直线应力锥进行电场数值分析,结果表明,所设计的单直线应力锥满足100 kV直流高温超导电缆运行要求。     

高温超导电缆终端恒温器研制

高温超导电缆终端恒温器是高温超导电缆终端系统的重要组成部分,其长期可靠稳定的运行将为整个系统的良好运转奠定坚实基础.文中对成功研制的高温超导电缆终端恒温器进行了详细介绍,包括技术指标及相关要求、总体结构、关键技术、热负荷分析与计算等.试验表明,高温超导电缆终端恒温器结构设计合理、操作方便;大口径可拆法兰低温真空压力环境下的密封技术得到突破、密封性能良好;低温液体输送管道承插密封结构设计新颖、满足工作要求.热负荷的分析与计算为高温超导电缆制冷系统所需冷量的确定提供了依据,同时也为终端恒温器的进一步优化指明了方向.     

高温超导电缆导体层电流分布研究

通过建立高温超导电缆等效电路模型,并提出电流分布等效数学方程,求得高温超导电缆导体层电流分布。绕制一根0.2m长110kV/2kA高温超导电缆样缆,并进行载流能力实验,得到各层电流分布结果。分析发现,各层电流分布的实验结果与理论计算结果吻合,从而验证电流分布计算模型的正确性,以及调整绕制角度对均匀层间分流的有效性。研究结论对以后更长高温超导电缆的载流能力分析具有一定的指导意义。     

35-110kV高温超导电缆终端低温恒温器热负荷分析

高温超导电缆终端是运行在低温的超导电缆芯向常温的高压母线过渡和制冷剂进出口的汇集组件,为了获得有效的超导电缆运行的低温环境,设计了一套电缆与终端可拆卸的恒温器,系统采用过冷液氮循环,液氮既是冷却介质,又是高电压绝缘介质。通过传热理论对恒温器的热负荷进行了计算,得到了用于35-110kV电压等级、额定电流交流2 000A的高温超导电缆低温恒温器主要漏热,尤其对终端交流电流引线进行了优化计算。计算结果表明,在现有设计结构下,恒温器的漏热量小于300W;从热负荷分布分析,电流引线漏热为主要漏热,支撑及传输管线的传导漏热占系统总漏热的22%左右。计算结果为该高温超导电缆终端低温系统的设计和进一步优化提供了依据。     

高温超导电缆在故障状态下的温升计算

为了更好地研究高温超导电缆在电力系统中的暂态过程,有必要研究高温超导电缆温升情况。从高温超导电缆的结构出发,分析了高温超导电缆的温度特性,建立了故障状态下高温超导电缆温度分布的数学计算模型,并通过MATLAB仿真软件对220kV高温超导电缆模型进行了仿真计算。结果表明高温超导电缆超导层与屏蔽层温度在系统发生三相短路时瞬间增大,但随着故障的解除而减小;超导层与屏蔽层电阻在瞬间增大之后会随温度的增大而增大。结果验证了所提出的电缆温度数学模型的可行性。     

10kV三相同轴高温超导电缆暂态电热特性分析

三相同轴高温超导电缆会受到电力系统中短路故障电流冲击,产生大量热,并可能被损坏.通过采用超导电缆各层的电流分布解析算法和温度分布数值计算法,构建了电缆仿真分析模型,包含电路模型、热模型和电热耦合模型.对10 kV/1.5 kA三相同轴高温超导电缆在20 kA,持续0.21 s故障电流冲击时的电流、电阻和温度分布进行计算...     

Application of the edge of chaos in combinatorial optimization

Many problems in science, engineering and real life are related to the combinatorial optimization. However, many combinatorial optimization problems belong to a class of the NP-hard problems, and their globally optimal solutions are usually difficult to solve. Therefore, great attention has been attracted to the algorithms of searching the globally optimal solution or near-optimal solution for the combinatorial optimization problems. As a typical combinatorial optimization problem, the traveling salesman problem(TSP) often serves as a touchstone for novel approaches. It has been found that natural systems, particularly brain nervous systems, work at the critical region between order and disorder, namely,on the edge of chaos. In this work, an algorithm for the combinatorial optimization problems is proposed based on the neural networks on the edge of chaos(ECNN). The algorithm is then applied to TSPs of 10 cities, 21 cities, 48 cities and 70 cities. The results show that ECNN algorithm has strong ability to drive the networks away from local minimums.Compared with the transiently chaotic neural network(TCNN), the stochastic chaotic neural network(SCNN) algorithms and other optimization algorithms, much higher rates of globally optimal solutions and near-optimal solutions are obtained with ECNN algorithm. To conclude, our algorithm provides an effective way for solving the combinatorial optimization problems.     

应用遗传算法和序列锥规划进行圆阵的方向图综合

为了解决圆阵方向图旁瓣电平较高的问题,提出了一种圆阵方向图综合方法。该方法将圆阵方向图的峰值旁瓣电平作为目标函数,首先采用改进遗传算法对阵元位置和阵元权值进行联合优化,不仅避免了算法的早熟收敛,而且符合理论意义上的全局最优。其次将遗传算法的优化结果作为初始迭代点,在其附近利用一阶泰勒级数将非凸的圆阵方向图综合问题转化为序列锥规划问题,以便采用凸优化理论进行高效求解。由于该算法增加了寻优操作的后期变异能力,因而有效提高了优化性能。最后仿真表明,阵元数一定的情况下,算法在进一步降低峰值旁瓣电平的同时,可有效减小其动态变化范围,使得圆阵方向图综合性能更优。     

一种采用优势个体多方向强制搜索策略的换热网络优化方法

提出一种采用优势个体多方向强制搜索策略的进化算法, 通过考察种群中个体差异性指标, 用以评价当前种群全局搜索的健康度。当优化结果出现长期停滞, 即健康度指标变差时, 启动优势个体多方向强制搜索策略, 扩大优势个体在靠近局部最优解区域的搜索方向, 保证算法全过程的全局搜索能力。用15SP和20SP算例进行验证, 与文献中最优结果相比, 分别下降了1.09%、0.83%, 表明优势个体多方向强制搜索策略充分发挥了优势个体的进化潜力, 提高了算法的优化效能。     

薄板弯曲大变形高阶非线性偏微分方程推导与优化算法研究

针对薄板弯曲大变形问题, 运用变分原理, 建立了薄板弯曲大变形问题的高阶非线性偏微分方程. 运用有限差分法和动态设计变量优化算法原理, 以离散坐标点的上未知挠度为设计变量, 以离散坐标点的差分方程组构建目标函数, 提出了薄板弯曲大变形挠度求解的动态设计变量优化算法, 编制了相应的优化求解程序. 分析了具有固定边界、均布载荷下的矩形薄板挠度的典型算例. 通过与有限元的结果对比, 表明了本文求解算法的有效性和精确性, 提供了直接求解实际工程问题的基础.     

大尺度分层介质电特性参数的反演方法研究

针对大尺度分层介质电磁场散射回波数据, 提出了一种用于分层介质特性参数反演的新方法, 实现了分层介质的介电常数、电导率和介质厚度的同时反演. 方法首先将这些参数的反演转化为最优化问题进行求解, 然后应用模拟退火算法搜索最优解, 充分利用算法的全局寻优能力, 同时改善了算法的搜索控制策略, 使算法在最优解的搜索过程中可以自适应地调整搜索步长, 提高了算法的搜索效率. 结果表明, 本文方法可以实现大尺度分层介质特性参数的准确反演, 且具有较强的抗噪声能力. 该方法可以应用于火星/月球 雷达探测回波数据的反演以及地下分层结构特性的分析. 关键词： 电磁散射 分层介质 模拟退火算法 最优化     

Optimization analysis on the bandwidth algorithm for the phase-locked loop (PLL) in OTU

The bandwidth of phase-locked loop (PLL) in optical transponder unit (OTU) is affected by both the external input jitter and the internal phase noise jitter, so the selection for the bandwidth of the PLL has a contradiction and it is necessary that the bandwidth is optimally designed. Under the consideration of both the external input jitter and the internal phase noise, the bandwidth algorithm of the PLL is comprehensively analyzed, and the optimization algorithm of the bandwidth for the PLL of the OTU can be deduced and obtained through improving the former calculation and analytical methods. The optimal bandwidth of the PLL has been analyzed and obtained so as to ensure that the clock output of the OTU has a lower jitter noise. And then the optimization algorithm is applied in 2.5 Gbit/s and 10 Gbit/s OTU, the optimal parameters of the PLL and the output jitter value of the OTU have been acquired by taking the quantitative and qualitative analysis of the PLL parameters. The study shows the optimization algorithm is superior and feasible as well as it is better used in the OTU and plays an important part in the practical application.     

Exergy-Based Multi-Objective Optimization of an Organic Rankine Cycle with a Zeotropic Mixture

In this paper, the performance of an organic Rankine cycle with a zeotropic mixture as a working fluid was evaluated using exergy-based methods: exergy, exergoeconomic, and exergoenvironmental analyses. The effect of system operation parameters and mixtures on the organic Rankine cycle’s performance was evaluated as well. The considered performances were the following: exergy efficiency, specific cost, and specific environmental effect of the net power generation. A multi-objective optimization approach was applied for parametric optimization. The approach was based on the particle swarm algorithm to find a set of Pareto optimal solutions. One final optimal solution was selected using a decision-making method. The optimization results indicated that the zeotropic mixture of cyclohexane/toluene had a higher thermodynamic and economic performance, while the benzene/toluene zeotropic mixture had the highest environmental performance. Finally, a comparative analysis of zeotropic mixtures and pure fluids was conducted. The organic Rankine cycle with the mixtures as working fluids showed significant improvement in energetic, economic, and environmental performances.     

Research on Fault Diagnosis of Rolling Bearings Based on Variational Mode Decomposition Improved by the Niche Genetic Algorithm

Due to the influence of signal-to-noise ratio in the early failure stage of rolling bearings in rotating machinery, it is difficult to effectively extract feature information. Variational Mode Decomposition (VMD) has been widely used to decompose vibration signals which can reflect more fault omens. In order to improve the efficiency and accuracy, a method to optimize VMD by using the Niche Genetic Algorithm (NGA) is proposed in this paper. In this method, the optimal Shannon entropy of modal components in a VMD algorithm is taken as the optimization objective, by using the NGA to constantly update and optimize the combination of influencing parameters composed of α and K so as to minimize the local minimum entropy. According to the obtained optimization results, the optimal input parameters of the VMD algorithm were set. The method mentioned is applied to the fault extraction of a simulated signal and a measured signal of a rolling bearing. The decomposition process of the rolling-bearing fault signal was transferred to the variational frame by the NGA-VMD algorithm, and several eigenmode function components were obtained. The energy feature extracted from the modal component containing the main fault information was used as the input vector of a particle swarm optimized support vector machine (PSO-SVM) and used to identify the fault type of the rolling bearing. The analysis results of the simulation signal and measured signal show that: the NGA-VMD algorithm can decompose the vibration signal of a rolling bearing accurately and has a better robust performance and correct recognition rate than the VMD algorithm. It can highlight the local characteristics of the original sample data and reduce the interference of the parameters selected artificially in the VMD algorithm on the processing results, improving the fault-diagnosis efficiency of rolling bearings.     

应用于光束均匀化整形的SAGAGD算法

 分析了模拟退火算法、基因算法、梯度下降法的主要步骤和应用中的优劣，将这三种方法加以综合运用于纯位相元件的优化设计以实现光束均匀化，结果表明，该算法对于设计位相光学元件是十分有效的。     

基于遗传模型改进蜂群算法的稀疏阵列优化

人工蜂群算法作为一种新兴的群体智能算法,在解决复杂连续问题时表现突出。但是由于算法本身内在运行机制的原因,算法在搜索上表现出优异的性能,却疏于开发。为了平衡搜索和开发二者之间的矛盾,提出了一种基于遗传模型改进的人工蜂群算法,并成功运用到了阵列综合领域。算法先将全局最优解引入邻域搜索过程,指导蜂群寻找最佳蜜源,加速算法收敛。为了避免人工蜂群算法陷入局部最优,需要提高其开发能力,通过借鉴遗传算法中的进化机制,建立了遗传模型,对采取最佳保留后的蜜源进行遗传操作,丰富蜜源的多样性。在一组广泛使用的数值函数上对改进人工蜂群算法进行了测试,实验数据表明,该算法相较于其他算法具有很强的竞争力。将该算法运用于线性阵列的稀疏优化,旨在降低阵列的峰值旁瓣电平,在同样的阵列约束下与其他算法进行了优化对比,仿真结果进一步证明了算法的有效性。