Artificial bee colony based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions

Artificial bee colony (ABC) algorithm has several characteristics that make it more attractive than other bio-inspired methods. Particularly, it is simple, it uses fewer control parameters and its convergence is independent of the initial conditions. In this paper, a novel artificial bee colony based maximum power point tracking algorithm (MPPT) is proposed. The developed algorithm, does not allow only overcoming the common drawback of the conventional MPPT methods, but it gives a simple and a robust MPPT scheme. A co-simulation methodology, combining Matlab/Simulink™ and Cadence/Pspice™, is used to verify the effectiveness of the proposed method and compare its performance, under dynamic weather conditions, with that of the Particle Swarm Optimization (PSO) based MPPT algorithm. Moreover, a laboratory setup has been realized and used to experimentally validate the proposed ABC-based MPPT algorithm. Simulation and experimental results have shown the satisfactory performance of the proposed approach.     

Study on maximum power point tracking of photovoltaic array in irregular shadow

Traditional maximum power point tracking (MPPT) methods can hardly find global maximum power point (MPP) because output characteristics curve of photovoltaic (PV) array may have multi local maximum power points in irregular shadow, and thus easily fall into the local maximum power point. To address this drawback, Considering that sliding mode variable structure (SMVS) control strategy have such advantages as simple structure, fast response and strong robustness, and P&O method have the advantages of simple principle and convenient implementation, so a new algorithm combining SMVS control method and P&O method is proposed, besides, PI controller is applied to reduce system chattering caused by switching sliding surface. It is applied to MPPT control of PV array in irregular shadow to solve the problem of multi-peak optimization in partial shadow. In order to verity the rationality of the proposed algorithm, the experimental circuit is built, which achieves MPPT control by means of the proposed algorithm and P&O method. The experimental results show that compared with the traditional P&O algorithm, the proposed algorithm can fast track the global MPP, tracking speed increases by 60% and the relative error decreased by 20%. Moreover, the system becomes more stable near the MPP, the fluctuations of output power is greatly reduced, and thus make full use of solar energy.     

基于深度学习的人体姿态估计方法综述

基于深度学习的人体姿态估计方法旨在通过构建合适的神经网络，直接从二维的图像特征中回归出人体姿态信息。主要按照2D人体姿态估计到3D人体姿态估计的顺序，并从单人检测与多人检测、稀疏的关节点检测与密集的模型构建等方面，对近年来基于深度学习的人体姿态估计方法进行系统介绍，从而初步了解如何通过深度学习的方法得到人体姿态的各个要素，包括肢体部件的相对朝向和比例尺度、骨骼关节点的位置坐标和连接关系，甚至更为复杂的人体蒙皮模型信息。最后,对当前研究面临的挑战以及未来的热点动向进行概述，清晰地呈现出该领域的发展脉络。     

Nb和时效时间对热轧中锰TRIP钢中P偏聚的影响

热轧态中锰TRIP钢首先经650 ℃退火2 h,随后在550 ℃进行等温时效热处理,采用场发射扫描电镜(FE-SEM)研究该钢中P的偏聚和时效析出行为的变化情况。结果表明,中锰TRIP钢中P在晶界的偏聚是一种非平衡偏聚现象,临界时间约为50 h,与理论计算结果48 h较为吻合。在局部偏聚区域内,C与P存在共偏聚的关系,即P偏聚量高的地方,C含量也高。而合金元素Nb具有抑制P偏聚的效果,在20~70 h时效时间内,可以相对降低6.57%~19.5%的最大P偏聚量。根据电子背散射衍射(EBSD)菊池线分析,P偏聚量低于2.28at%时,P为固溶状态,高于2.28at.%时,P为析出状态。     

因素空间理论下基点分类算法研究

目前，基于因素空间理论的背景基提取算法计算过程复杂，初始化必须依赖各因素极值，基点数量提取冗余等原因，未能在应用中取得很好效果。为此，结合内点判别法和知识可继承、可扩展的思想，提出一种计算简单、初始化独立、基点数量小的改进的背景基提取算法。然后，利用改进的背景基提取算法构造出一种全新的数据分类算法-基点分类算法，基点分类算法以提取每一类样本的背景基为预测模型，再通过新定义的λ-背景基，优化预测模型。数值实验表明:基点分类算法原理简单、构造难度小、分类模型泛化能力强，预测能力准确率高，同时严格的模型限定区域又能为识别新类别提供新方法。     

离心泵并联运行工况点的数值求解

建立了求解多台不同型号离心泵并联运行工况点的数学模型,给出了用数值计算中的“二分法”求解该模型的方法,并附有用Exce l计算的实例。     

Microstructures and Phase Transition Points of As-Cast Mg-Zn-Y System Alloys

As-east mierostruetures and their distribution of Mg-Zn-Y ternary alloy with high magnesium, low zinc and yttrium were examined using Nikon Epiphot optical microscopy （OM）, RigakuD/max-3C X- ray diffraetion （XRD）, and JEOL JSM-6700F scanning electron microscopy （SEM） equipped with an energydispersive X-ray spectroscopy （EDS）. In the as-east mierostructures, Yttrium and zinc tend to segregate at grain boundaries,     

泥页岩井壁稳定研究及在临盘地区的应用

从岩石力学和物理化学两个主要因素简要分析了井壁失稳的机理，指出泥页岩井壁失稳是由力学与化学两方面因素共同作用的结果。钻井液与泥页岩存在化学势差，并改变了井壁附近的孔隙压力，降低岩石强度。借助于井壁处有效应力的变化,将泥页岩与钻井液相互作用时页岩水化所产生的力学效应与纯力学效应结合起来，计算出任意井斜方位井眼围岩应力状态，利用测井资料求出有关岩石力学参数和Mohr Couloumb准则，计算得出防塌的临界钻井液密度。     

红外光谱法用于快速测定车用柴油酸度等性质的研究

针对车用柴油酸度等性质测定过程繁琐，采用衰减全反射样品池测定车用柴油的红外光谱，用偏最小二乘法（PLS）建立红外光谱测定车用柴油酸度、密度、闪点和凝点的4个校正模型，验证标准误差分别为0.46 mg/(100 mL),0.77kg/m3,2.60 ℃,2.77 ℃，该方法符合标准方法再现性要求。与标准方法相比，该方法具有无需预处理、操作简单、测量快速、重复性好等优点。     

蜡晶形态结构对原油降凝的影响

 采用偏光显微镜观察了不同条件下蜡晶的形态变化，对蜡结晶过程中的结构、分布状态和生长规律进行了深入的研究，采用气相色谱分析了用52#、62#、80#蜡配制的模拟油中蜡的碳数分布，考察了凝点与蜡含量之间的变化规律，以及沥青质、胶质和大分子降凝剂(PPD)对模拟油降凝、降粘的影响，为改善原油流动性提供理论依据。实验结果表明，蜡晶的微观形态结构、蜡在油中的溶解性能以及降凝剂的降凝作用与模拟油中蜡的碳数分布密切相关，只有当降凝剂分子结构与油中蜡的结构匹配时，才能达到理想的降凝效果。通过实验确定了模拟油降凝时的临界蜡含量为40%（质量分数），大于该临界值后，凝点随着蜡含量的变化幅度将大大降低。