木材断裂解离分形特征与分形断裂力学模型研究

目的 以椴木为研究对象,研究冲击载荷作用下椴木试件的断裂解离形貌特征和断裂力学特性,建立适用于木材原料断裂解离的分形断裂力学模型,并对其断裂解离力学行为进行描述。方法 对椴木试件进行冲击加载试验,分析试件断口的形貌特征和断裂力学特性,构建适用于木材原料断裂解离的分形断裂力学模型。结果 椴木试件横向冲击断裂断口裂纹形状和断口形貌特征比纵向冲击复杂,横、纵向冲击断裂断口均具有分形特征;椴木试件纵向冲击断裂韧性均值是横向冲击断裂韧性均值的1.112倍,椴木试件横、纵向冲击断口的分形维数均值分别为2.063 5和2.075 1,椴木试件横、纵向冲击韧性与其断口分形维数之间存在线性正相关关系,拟合优度分别为0.778 7和0.812 2;构建的木材原料断裂解离临界解离应力和断裂韧性的分形断裂力学模型也适用于脆性材料。结论 在木材原料冲击断裂解离时,木材原料初始裂纹长度越短,断裂解离断口越粗糙复杂,木材原料断裂解离所需要的能量越大;当裂纹沿着与冲击加载力方向垂直成大约1.055rad方向扩展时所需的能量最小,木材原料最易沿该方向进行断裂解离。     

基于改进正余弦优化算法的多阈值图像分割

针对多阈值图像分割方法计算量大、分割精度低的问题,提出了基于改进正余弦算法（improved sine cosine algorithm,ISCA）的多阈值图像分割方法。首先对种群进行混沌初始化来提高初始种群质量;其次根据粒子适应度值的大小自适应地调整参数;最后引入反向学习策略并择优选取粒子。伯克利图像和植物冠层图像分割实验的结果表明,该算法的运行时间较短,而且分割精度较高,具有较强的鲁棒性。     

改进萤火虫优化算法的Renyi熵污油图像分割

针对传统Renyi熵方法在分割污油图像时存在图片差距大、无法根据不同图片进行最优分割的问题,提出改进萤火虫算法对二维Renyi熵分割算法中的α值进行寻优来解决上述问题。分析了采集的污油图片特点以及对污油图片进行分割的必要性;针对多目标寻优精度不高和后期收敛速度较慢的问题,对萤火虫算法进行了改进,并对初始萤火虫位置进行混沌优化处理,使结果达到全局最优;利用基于改进萤火虫算法的Renyi熵图像分割算法对采集的污油图片进行阈值分割实验,并与二维Renyi熵分割、粒子群算法(PSO)Renyi熵分割方法进行比较。实验结果表明:本文提出的算法可以有效地对污油区域进行分割,能够快速地实现复杂图像的精确处理。     

UAV Clustering Scheme for FANETs using Elbow-Hybrid Metaheuristic Techniques

Great strides have been made to realistically deploy multiple Unmanned Aerial Vehicles (UAVs) within the commercial domain, which demands a proper coordination and reliable communication among the UAVs. UAVs suffer from limited time of flight. Conventional techniques suffer from high delay, low throughput, and early node death due to aerial topology of UAV networks. To deal with these issues, this paper proposes a UAV parameter vector which considers node energy, channel state information and mobility of UAVs. By intelligently estimating the proposed parameter, the state of UAV can be predicted closely. Accordingly, efficient clustering may be achieved by using suitable metaheuristic techniques. In the current work, Elbow method has been used to determine optimal cluster count in the deployed FANET. The proposed UAV parameter vector is then integrated into two popular hybrid metaheuristic algorithms, namely, water cycle-moth flame optimization (WCMFO) and Grey Wolf-Particle Swarm optimization (GWPSO), thereby enhancing the lifespan of the system. A methodology based on the holistic approach of parameter and signal formulation, estimation model for intelligent clustering, and statistical parameters for performance analysis is carried out by the energy consumption of the network and the alive node analysis. Rigorous simulations are run to demonstrate node density variations to validate the theoretical developments for various proportions of network system sizes. The proposed method presents significant improvement over conventional state-of-the-art methods.     

Manipulation planning using learned symbolic state abstractions

We present an approach for planning robotic manipulation tasks that uses a learned mapping between geometric states and logical predicates. Manipulation planning, because it requires task-level and geometric reasoning, requires such a mapping to convert between the two. Consider a robot tasked with putting several cups on a tray. The robot needs to find positions for all the objects, and may need to nest one cup inside another to get them all on the tray. This requires translating back and forth between symbolic states that the planner uses, such as stacked (cup1,cup2), and geometric states representing the positions and poses of the objects. We learn the mapping from labelled examples, and importantly learn a representation that can be used in both the forward (from geometric to symbolic) and reverse directions. This enables us to build symbolic representations of scenes the robot observes, but also to translate a desired symbolic state from a plan into a geometric state that the robot can achieve through manipulation. We also show how such a mapping can be used for efficient manipulation planning: the planner first plans symbolically, then applies the mapping to generate geometric positions that are then sent to a path planner.     

水稻调亏灌溉Fuzzy-PID智能监控系统研究

灌溉的自动控制是一个大惯性、纯滞后、非线性的过程,难以用精确的数学表达式来描述,常规的PID控制方法很难完成这种任务.针对水稻调亏灌溉的控制要求,提出将田间水位或土壤含水率与设定值比较获得差值及其变化率作为系统的输入,水泵及电动阀门是否打开作为系统的输出,建立Fuzzy-PID智能监控系统.试验证明Fuzzy-PID控...     

Microstructure of ZM6 magnesium alloy with different Nd content

With the purpose of studying the influence of Nd on the alloy structure and castability of ZM6, under the fixed content of Zn and Zr, this paper observes and analyzes the microstructure morphology of ZM6 alloy fracture with different Nd content by the means of uniaxial tension experiment and scanning electron microscope (SEM) observation. The search results indicate that the structure of ZM6 alloy after added Nd can be refined to some extent, while it has no obvious influence on the grain structure and dimension of asast ZM6 alloy. Through increasing the ratio between Nd and Zn, it turns out that Nd and Zn reduces their own solid solubility by each other in a-Mg, and meanwhile, they gather toward the grain boundary, which is beneficial to refine the structure of ZM6 alloy ingot and enables the grain dimension of ZM6 alloy to reach the minimum when the Nd content is 2.5 %. On the basis of the minimization of the grain dimension, the tensile property of ZM6 alloy improves with the Nd content. Thus, it provides theoretical guidance and technical support for the improvement of ZM6 alloy structure.     

木地板码垛机械手末端夹持机构设计及运动学仿真

论文设计了一款可以一次性抓取多块木地板的末端夹持型执行机构。运用Solid Works三维制图软件建立了机械手末端执行机构的三维模型。并运用ADAMS仿真软件对机械手末端夹持机构的三维模型进行运动学分析。结果表明,论文所设计的机械手末端夹持机构能够平稳抓取和放开板材,达到使用要求。     

基于小波神经网络的木材干燥窑内传感器建模研究

针对木材干燥系统具有非线性、强耦合的特性,难以建立准确的数学模型,提出一种基于小波神经网络的建模方法。通过木材干燥窑内木材含水率传感器、温度传感器和湿度传感器采集的数据建立小波神经网络模型,并通过模型预测木材含水率传感器的测量值。小波神经网络将BP神经网络在非线性问题上自学习的能力与小波表征信号局部信息的能力相结合,具有很强的自适应分辨性和容错能力。利用实际木材干燥过程中采集的数据作为训练样本进行仿真实验。结果表明：小波神经网络方法建立的模型能够预测木材含水率传感器的测量值,模型泛化能力强,预测精度高于BP神经网络建立的模型,验证了小波神经网络对木材干燥窑内传感器建模的可行性和有效性。     

基于双五次多项式的智能汽车换道路径规划研究

快速准确地进行换道路径规划、有效跟踪期望路径以及换道过程中保持车辆的操纵稳定性,是保障智能汽车主动安全的核心技术.针对智能汽车主动换道过程中的路径规划问题,引入中转位置,提出基于双五次多项式的路径规划策略,以提高换道路径的平滑性,保证车辆换道安全性,满足换道实时性要求.对主动换道场景进行分析,确定换道初始及目标位置;基于车辆换道过程中的临界碰撞点,提出双五次多项式换道路径规划策略;建立联合仿真模型,针对不同道路状态进行主动换道仿真试验.结果表明：由于引入了中转点,利用双五次多项式规划方法得到的换道路径在临界碰撞状态前有更明显的侧向位移,能避开前方障碍车保证了换道安全性;换道中转位置处车辆最大侧向加速度不超过2 m/s²,保证了换道过程中车辆操纵稳定性;在干燥路面与湿润路面工况下,换道所需纵向安全距离减小20 m左右,保障了换道过程的纵向碰撞的安全性.研究结果可以为智能汽车主动换道路径规划提供理论及实践依据.