排序方式: 共有20条查询结果,搜索用时 15 毫秒
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提出一种三维水翼的优化设计方法.方法应用混合粒子群算法(HPSO)与边界元法相结合进行三维水翼的优化和性能计算工作、应用多级罚函数法解决水翼设计这一多约束、多变量的优化问题.基于免疫理论和惯性权值非线性递减策略的混合微粒群算法,能够有效抑制算法早熟收敛,平衡全局和局部搜索能力.优化设计过程中,水翼的剖面形状、攻角及展弦比作为设计变量,给定的压力分布形式、升阻力系数作为设计约束或设计目标.混合粒子群算法通过划分子种群、应用基于MPI通信机制的并行计算来实施,最大限度减小了计算时间.设计算例表明了文中提出的三维水翼优化设计方法收敛速度快、计算时间短、有效可行. 相似文献
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为了适用于大范围海洋环境下须要考虑能量耗尽问题的AUV导航,提出了一种考虑海流影响的水下机器人全局路径规划方法,该方法将海流因素作为GA算法的评价因子,在路径规划的层面上考虑海流的影响;在此基础上对GA算法进行了改进,提出一种GA-PSO混合算法,GA-PSO混合算法比单纯的GA算法具有更快的收敛速度和运行效率。 相似文献
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一种基于CFD的水动力系数计算新方法(英文) 总被引:3,自引:0,他引:3
Applications of computational fluid dynamic (CFD) to the maritime industry continue to grow with the increasing development
of computers. Numerical approaches have evolved to a level of accuracy which allows them to be applied for hydrodynamic computations
in industry areas. Hydrodynamic tests, especially planar-motion-mechanism (PMM) tests are simulated by CFD software -FLUENT,
and all of the corresponding hydrodynamic coefficients are obtained, which satisfy the need of establishing the simulation
system to evaluate maneuverability of vehicles during the autonomous underwater vehicle scheme design stage. The established
simulation system performed well in tests. 相似文献
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欠驱动AUV的运动控制技术综述 总被引:4,自引:0,他引:4
欠驱动水下机器人由于在减轻系统质量、节约成本和能耗以及提高系统可靠性等方面的优点日益成为研究的热点。尤其是在水下机器人在海洋能源开发中发挥着不可或缺作用的今天,利用少于位形空间维数的控制输入控制欠驱动系统的运动具有非常重要的现实意义。结合水下机器人自身的运动特性,归纳了欠驱动AUV的控制特性,包括本质非线性、欠驱动特性、可控性、约束特性、平衡点特性等。综述了目前欠驱动AUV运动控制技术的主要研究成果,主要包括镇定控制和跟踪控制,并对今后欠驱动AUV的理论与应用发展方向进行了展望。 相似文献
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微小型潜器空间运动建模与仿真(英文) 总被引:3,自引:1,他引:2
对自主式潜器空间运动进行精确建模和仿真对研究其操纵和控制特性有重要意义,本文以开发的"MAUV-Ⅱ"微小型潜器为对象,基于动量定理和动量矩定理建立了潜器空间运动的非线性数学模型,将潜器受力分解为各个模块并表达为矩阵形式.在运动非线性数学模型的基础上,结合虚拟现实技术建立了运动仿真系统,针对所研究潜器的特点,采用S面控制方法对此"MAUV-Ⅱ"水下运动的艏向控制和深度控制进行了仿真研究,同时进行了基于目标规划的长距离航行仿真试验.仿真结果反映了潜器具有较好的空间操纵性能,也验证了控制软件的可行性和可靠性. 相似文献
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根据管理标准的要求,结合多年从事管理、审核工作的经验与体会,作者对企业在根据国际管理体系标准,建立与实施管理体系过程中经常遇到的几个问题,提出了自己的观点与建议. 相似文献
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一种基于PSO优化HWFCM的快速水下图像分割算法 总被引:3,自引:0,他引:3
The S/N of an underwater image is low and has a fuzzy edge.If using traditional methods to process it directly,the result is not satisfying.Though the traditional fuzzy C-means algorithm can sometimes divide the image into object and background,its time-consuming computation is often an obstacle.The mission of the vision system of an autonomous underwater vehicle (AUV) is to rapidly and exactly deal with the information about the object in a complex environment for the AUV to use the obtained result to execute the next task.So,by using the statistical characteristics of the gray image histogram,a fast and effective fuzzy C-means underwater image segmentation algorithm was presented.With the weighted histogram modifying the fuzzy membership,the above algorithm can not only cut down on a large amount of data processing and storage during the computation process compared with the traditional algorithm,so as to speed up the efficiency of the segmentation,but also improve the quality of underwater image segmentation.Finally,particle swarm optimization (PSO) described by the sine function was introduced to the algorithm mentioned above.It made up for the shortcomings that the FCM algorithm can not get the global optimal solution.Thus,on the one hand,it considers the global impact and achieves the local optimal solution,and on the other hand,further greatly increases the computing speed.Experimental results indicate that the novel algorithm can reach a better segmentation quality and the processing time of each image is reduced.They enhance efficiency and satisfy the requirements of a highly effective,real-time AUV. 相似文献