基于接触力识别的人机协作控制系统设计与实现

为实现人机协作搬运,设计了一种基于接触力操作意图识别的搬运机器人原型机.以直联方式设计由刚性杆和伺服电机构成的单自由度运动机械臂,研究位置控制器,实现扭矩工作模式下的闭环控制.为获取操作意图信息,在刚性杆末端两侧分别设置FSR薄膜压力传感器,用于检测操作者与机械臂的短暂接触力.对应3种常见操作情况给出相应时域算法提取接...     

基于装载能力约束的集货车辆路径问题研究

针对物流货运过程中,集货车辆在规定时间内从各配货站集货后回到中心货站进行分类运输问题建立了多目标组合优化模型,并设计了相应的算法。通过实证模拟的方式检验了所提出了基于装载能力约束的集货车辆路径优化方案,为物流中心集货车辆的优化调度提供理论指导和实际借鉴作用。     

基于“货到人”拣选模式的储位分配问题研究

研究了“货到人”拣选模式下的储位分配问题,以订单拣选过程中搬运货架总时间最短为目标建立了整数非线性规划模型,并证明其为NP-hard问题,分别设计了求解模型的贪婪算法和单亲进化遗传算法。首先根据订单和物品的关联关系对物品进行聚类,基于聚类结果设计了求解模型的贪婪算法。然后设计了直接求解模型的单亲进化遗传算法,遗传算法中采用了0-1矩阵编码、多点基因倒位算子、单点基因突变算子和精英保留等策略,通过合理选取参数,能够很快求解出问题的近似最优解。最后利用模拟算例和一个具体实例进行计算,并对贪婪算法和遗传算法的求解时间和求解效果进行了比较分析。结果显示,对于小规模问题,两种算法均能在较短的时间内以很高的概率得到问题的全局最优解,对于中等规模的实际问题,利用两种算法得到的储位分配方案均优于企业目前采取的基于出库频率的储位分配方案,遗传算法得到的储位分配方案对应的货架搬运次数、货架搬运总时间等均优于贪婪算法。本文设计的遗传算法可以作为智能仓库管理信息系统的核心算法。     

基于非均质多相流模型的液舱晃荡数值模拟

应用非均质多相流模型对不同装载率和激励频率下矩形液舱的横摇晃荡运动进行了数值模拟.分析了液体重心的横向和纵向运动情况,计算了不同工况下自由液面形状与速度场分布以及舱壁测点处压力的时间历程和相应的功率谱密度.模拟结果与均质模型计算结果和试验结果的对比分析验证了非均质模型在模拟液舱晃荡时的优越性.     

现代油船液货系统气体管网工况仿真研究

针对现代油船液货系统气体管网的特点，将大压差气体管道流动模型应用于管元，将有限元理论应用于管网系统，建立了仿真模型；通过仿真气体管网的实际工况，验证了模型的可靠性和实用性；形成的软件丰富了油船模拟器项目的内容并为油船优化作业提供了平台。     

Cooperative dynamics of coupled motor–cargoes system with stochastic interactions in the crowded environment

In this study, we investigate the cooperative transport behaviors of coupled motor–cargoes system, in which multiple passive cargoes stochastically interact with one active Brownian motor. The environment with stochastic interactions is characterized by the concentration (reflecting the cargo’s number in unit volume) and switching rate (reflecting the interacting stability between motor and cargoes), based on which the stationary multiple-state process can be employed to describe the fluctuating-cargo state in the coupled system. By analyzing the average probability current of decoupled system in the thermodynamic limit, we effectively study the possibility of cooperative transport through stochastic cargoes to behave rich dynamical behaviors, including the directed current, current reversal, stochastic resonance (SR) and stochastic inhibition (SI), inverse SR and SI, even without the effect of external driving force. Based on numerical results, we systematically discuss the transport dependence on various parameters, including the cargo concentration in the crowded environment, cargo capacity of the motor, driving amplitude of external periodic force, and medium temperature. Obviously, the sensitivity of transport process to parameter changes can be used by the environment to regulate its cargo traffic, which also provides latent support for manipulating the transport performance and optimizing the coupled structure in artificial nano-machines.     

货油舱用耐蚀钢连续冷却的转变规律

在MMS-300热模拟试验机上测得货油舱用耐蚀钢在不同冷速下的连续冷却膨胀曲线,结合金相-硬度法,研究了该耐蚀钢变形和未变形过冷奥氏体冷却过程中的组织演变,建立了连续冷却转变(CCT)曲线.结果表明,动态CCT曲线较静态CCT曲线明显向左上方移动,提高了奥氏体转变的开始温度;随着冷却速度的增大,显微组织由多边形铁素体、珠光体和少量贝氏体逐渐过渡到针状铁素体、粒状贝氏体,最后为板条贝氏体和马氏体.     

Comments on paratrooper‐separation modeling with the DSD/SST formulation and FOIST

We provide a brief chronological background on the deforming‐spatial‐domain/stabilized space–time (DSD/SST) formulation, its use in aerodynamic modeling of a paratrooper separating from an aircraft, and the fluid–object interactions subcomputation technique (FOIST). Copyright © 2010 John Wiley & Sons, Ltd.     

基于温度应力场的沥青船货舱结构强度分析

以4 000 DWT沥青船货舱结构为例,建立有限元模型,考虑温度应力场影响,对沥青船的2种工况进行有限元计算分析。结果表明结构满足强度要求,为运载高温液货的沥青船结构设计提供了重要的设计参考。     

Model and algorithms for multi-period sea cargo mix problem

In this paper, we consider the sea cargo mix problem in international ocean container shipping industry. We describe the characteristics of the cargo mix problem for the carrier in a multi-period planning horizon, and formulate it as a multi-dimensional multiple knapsack problem (MDMKP). In particular, the MDMKP is an optimization model that maximizes the total profit generated by all freight bookings accepted in a multi-period planning horizon subject to the limited shipping capacities. We propose two heuristic algorithms that can solve large scale problems with tens of thousands of decision variables in a short time. Finally, numerical experiments on a wide range of randomly generated problem instances are conducted to demonstrate the efficiency of the algorithms.