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Optimization of closing law of turbine guide vanes based on improved artificial ecosystem algorithm

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Journal of Hydrodynamics 2023年第3期35卷 582-593页

作者： Li-ying Wang Jia-jie Zhang Hong-gang Fan College of Water Conservancy and Hydropower Hebei University of EngineeringHandan 056038China Hebei Key Laboratory of Smart Water Conservancy Handan 056038China State Key Laboratory of Hydroscience and Engineering Department of Energy and Power EngineeringTsinghua UniversityBeijing 100084China

Optimization of the closing law of the guide vane is the most economical and efficient way to reduce the risk incurred by pressure and speed excursions,thus guaranteeing the security of the hydro-turbine and the whole hydraulic *** order to optimize the closing law of the guide vane of hydraulic turbine,an improved artificial ecosystem optimization algorithm was proposed(IAEO).The reverse learning was used to initialize the population,multi-strategy bound handing schemes was used to improve the algorithm convergence ***-three mathematical benchmark functions were used to test the *** showed an improvement in the IAEO algorithm convergence speed and a stronger exploration than other *** algorithm was used to optimize the closing law of the guide vane of hydraulic turbine based on the hydraulic transient *** results showed that the maximum pressure in the spiral casing inlet,the minimum pressure in the draft tube inlet and the maximum speed all meet the design requirements by use of the closing law of the guide vane optimized by *** with other algorithms such as particle swarm optimization(PSO),artificial ecosystem-based optimization(AEO)and grey wolf optimizer(GWO),the closing law of the guide vane optimized by IAEO algorithm was proved to be of great advantages in distribution of safety margin of each optimization goal.

关键词： Hydraulic transient process the closing law of guide vane improved artificial ecosystem-based optimization(IAEO) optimization calculation

Adaptive PID Control for Hydraulic Turbine Regulation Systems Based on INGWO and BPNN

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Protection and Control of Modern Power Systems 2024年第4期9卷 126-146页

作者： Jinbao Chen gang He Yunhe Wang Yang Zheng Zhihuai Xiao the China Yangtze River Electric Power Co. Ltd.Wuhan 430000China the School of Power and Mechanical Engineering Wuhan UniversityWuhan 430072China the Hebei Fengning Pumped Storage Co. Ltd.Chengde 050300China

To ensure system stability,the fixed-PID(F-PID)controller with small parameters is usually adopted in hydropower *** involves a slow setting speed and it is difficult to realize optimal control for full working *** address the problem,this paper designs a variable-PID(V-PID)controller for a hydraulic turbine regulation system(HTRS)based on the improved grey wolf optimizer(INGWO)and back propagation neural networks(BPNN).These can achieve excellent regulation under full working ***,the nonlinear HTRS model containing the nonlinear hydroturbine model is constructed and the stable domain is obtained using Hopf bifurcation theory to determine the available range of PID *** optimal PID parameters in typical working conditions are then calculated by the INGWO,and the optimal PID parameters are generalized through training the V-PID neural networks which take the optimal PID parameters as sample *** V-PID neural networks with different structures are compared to determine the optimal structure of the variable-PID controller *** V-PID controller-based nonlinear HTRS model shows that the PID parameters can be automatically adjusted online according to the working condition changes,realizing optimal control of hydropower units in full working conditions.

关键词： Hydraulic turbine regulation system back propagation neural networks Hopf bifurcation grey wolf optimizer variable-PID controller

A novel grey wolf optimizer and its applications in 5G frequency selection surface design

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Frontiers of Information Technology & Electronic Engineering 2022年第9期23卷 1338-1353页

作者： Zhihao HE gang JIN Yingjun WANG National Engineering Research Center of Novel Equipment for Polymer Processing South China University of TechnologyGuangzhou510641China Key Laboratory of Polymer Processing Engineering of the Ministry of Education South China University of TechnologyGuangzhou510641China Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing South China University of TechnologyGuangzhou510641China

In fifth-generation wireless communication system(5G),more connections are built between metaheuristics and electromagnetic equipment *** this paper,we propose a self-adaptive grey wolf optimizer(SAGWO)combined with a novel optimization model of a 5G frequency selection surface(FSS)based on FSS unit *** includes three improvement strategies,improving the initial distribution,increasing the randomness,and enhancing the local search,to accelerate the convergence and effectively avoid local *** benchmark tests,the proposed optimizer performs better than the five other optimization algorithms:original grey wolf optimizer(GWO),genetic algorithm(GA),particle swarm optimizer(PSO),improved grey wolf optimizer(IGWO),and selective opposition based grey wolf optimization(SOGWO).Due to its global searchability,SAGWO is suitable for solving the optimization problem of a 5G FSS that has a large design *** combination of SAGWO and the new FSS optimization model can automatically obtain the shape of the FSS unit with electromagnetic interference shielding capability at the center operating *** verify the performance of the proposed method,a double-layer ring FSS is designed with the purpose of providing electromagnetic interference shielding features at28 *** results show that the optimized FSS has better electromagnetic interference shielding at the center frequency and has higher angular ***,a sample of the optimized FSS is fabricated and tested.

关键词： Grey wolf optimizer Fifth-generation wireless communication system(5G) Frequency selection surface Shape optimization

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算子的拟相似性与本质谱的性质

Journal of Mathematical Research and Exposition 2006年第3期26卷 571-575页

作者：苏维钢福建师范大学数学与计算机科学学院福建福州350007

设算子A和B拟相似,本文通过算子谱的精密结构的分析,给出了算子A的wolf本质谱、Kato本质谱、Weyl本质谱以及右本质谱的连通分支与算子B的wolf本质谱的某些子集的相交关系,并肯定地回答了***在文献[3]中提出的一个问题．

关键词：有界线性算子拟相似本质谱连通分支

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5MW风力机地震工况塔架动力学响应研究

动力工程学报 2017年第11期37卷 938-944页

作者：杨阳李春袁全勇上海理工大学能源与动力工程学院上海200093 上海市动力工程多相流动与传热重点实验室上海200093

基于FAST开源软件和wolf土-构耦合(SSI)模型建立了风力机地震工况动力学仿真模型,并计算了5种不同平均风速的气动载荷与101种不同强度的地震载荷联合作用下风力机的动力学响应.结果表明:在额定风速下,气动载荷与地震载荷之间为非线性耦... 详细信息

基于FAST开源软件和wolf土-构耦合(SSI)模型建立了风力机地震工况动力学仿真模型,并计算了5种不同平均风速的气动载荷与101种不同强度的地震载荷联合作用下风力机的动力学响应.结果表明:在额定风速下,气动载荷与地震载荷之间为非线性耦合,评估风力机地震动力学响应时,必须充分考虑风-震耦合效应;风速相同时,塔基最大弯矩先保持不变,再以线性增长的趋势变化;在低强度地震时,塔架不同高度处的最大弯矩与塔架高度之间为线性关系;随着地震强度的逐渐增大,塔架最大弯矩与塔架高度之间的关系逐渐变为非线性,且额定风速下塔架最大弯矩最大.

关键词：风力机地震载荷动力学响应架结构强度

DDPG方法在抖振约束下变弯度翼型/机翼设计的应用研究

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应用数学和力学 2024年第1期45卷 45-60页

作者：周思历孙刚王聪复旦大学航空航天系上海200433

变弯度技术可以提升巡航多升力系数工况下的升阻性能,对于提高整段巡航的经济效益具有重要意义.构造了光滑连续的流动分离函数约束翼型抖振性能,结合变弯度技术与人工神经网络代理模型搭建了某机翼截面翼型的巡航多升力系数工况优化模型... 详细信息

变弯度技术可以提升巡航多升力系数工况下的升阻性能,对于提高整段巡航的经济效益具有重要意义.构造了光滑连续的流动分离函数约束翼型抖振性能,结合变弯度技术与人工神经网络代理模型搭建了某机翼截面翼型的巡航多升力系数工况优化模型.应用深度确定性策略梯度(DDPG)方法优化此模型,实现了抖振约束下6.8%的巡航平均升阻比提升,优于粒子群和改进灰狼算法对此模型的优化结果.以优化前后翼型分别生成锥形后掠翼,验证了二维翼型变弯度优化对三维机翼的贡献.

关键词：气动外形优化 DDPG 变弯度抖振

改进灰狼算法在土壤墒情监测预测系统中的应用

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计算机应用 2017年第4期37卷 1202-1206页

作者：李宁李刚邓中亮北京邮电大学电子工程学院北京100876

针对现有的固定端传感器土壤墒情监测预测系统架设成本高、传感器易损坏、预测精度较低等问题,设计并实现了基于非固定无线传感器组网与改进灰狼算法优化神经网络的土壤墒情监测预测系统。系统使用非固定即插即用式传感器蓝牙组网收集... 详细信息

针对现有的固定端传感器土壤墒情监测预测系统架设成本高、传感器易损坏、预测精度较低等问题,设计并实现了基于非固定无线传感器组网与改进灰狼算法优化神经网络的土壤墒情监测预测系统。系统使用非固定即插即用式传感器蓝牙组网收集墒情数据,使用高精度多源定位接入融合方法进行广域室外高精度定位。在算法方面,针对灰狼算法在迭代中后期易陷入局部最优等问题,提出一种基于末尾探索者策略的改进灰狼算法。首先,根据种群个体适应度值排名,在原有算法个体类型中增加探索者类型。然后,将种群搜索分为三个时期:活跃探索期、周期探索期和种群回归期。最后,在每个时期使用特有的位置更新策略进行探索者位置调整,使得算法在探索初期更具随机性,在探索中后期依然保持一定的解空间搜索能力,从而增强算法的局部最优回避能力。使用标准函数进行算法性能测试,并将该算法应用于优化土壤墒情神经网络预测模型问题,使用某市2号试验田的数据进行实验。实验结果表明,所提算法与直接神经网络预测模型相比,相对误差下降约4个百分点;与传统灰狼算法、粒子群优化(PSO)算法优化模型比较,相对误差下降约1至2个百分点。所提算法拥有更小的误差,更好的局部最优回避能力,能有效提高墒情的预测质量。

关键词：土壤墒情预测系统灰狼优化算法神经网络高精度多源定位传感器网络

全矢融合的二元PELCD样本熵列车故障诊断

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噪声与振动控制 2024年第3期44卷 125-131页

作者：郑航李刚李德仓兰州交通大学机电技术研究所兰州730070 兰州交通大学甘肃省物流及运输装备信息化工程技术研究中心兰州730070 兰州交通大学甘肃省物流与运输装备行业技术中心兰州730070

长期高速运行的服役状态会造成高速列车转向架关键部件性能蜕化甚至发生故障等情况,所导致的安全事件将造成严重的经济损失甚至人员伤亡。考虑到高速列车振动信号的特性,将部分集成的局部特征尺度分解方法拓展至二元信号处理领域,同时... 详细信息

长期高速运行的服役状态会造成高速列车转向架关键部件性能蜕化甚至发生故障等情况,所导致的安全事件将造成严重的经济损失甚至人员伤亡。考虑到高速列车振动信号的特性,将部分集成的局部特征尺度分解方法拓展至二元信号处理领域,同时结合全矢谱理论对同阶分量信号进行信息融合,得到更加完备的数据特征,并对融合后的数据进行样本熵特征提取,得到列车的故障特征;采用灰狼优化算法对支持向量机进行参数寻优,通过实验对比单一故障工况、复合故障工况以及部件性能退化下的故障识别率,验证所提方法的有效性、优越性。

关键词：故障诊断二元部分集成的局部特征尺度分解方法全矢理论灰狼优化算法支持向量机

国产动画电影《喜羊羊与灰太狼》的成功启示录

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电影评介 2009年第17期 26-27页

作者：王纲安徽财经大学文学与艺术传媒学院

2009年开春,一部成本仅为区区600万元的动画电影《喜羊羊与灰太狼》创造了9000多万元的高额票房收入,引发广泛关注。探讨其中的成功因素,对于国产动画电影进一步发展具有重要启示。

关键词：动画电影票房启示