薄壁金属管是发生碰撞时为安全性所设置的关键吸能构件。为了提高薄壁管结构的耐撞性,结合方管的易安装性和圆管的稳定性,基于方竹结构对薄壁管截面进行耐撞性分析和仿生优化设计。通过对方竹结构的原型分析,利用ABAQUS搭建了仿方竹结...薄壁金属管是发生碰撞时为安全性所设置的关键吸能构件。为了提高薄壁管结构的耐撞性,结合方管的易安装性和圆管的稳定性,基于方竹结构对薄壁管截面进行耐撞性分析和仿生优化设计。通过对方竹结构的原型分析,利用ABAQUS搭建了仿方竹结构薄壁管有限元分析模型,在对模型进行试验验证的基础上,以壁厚、肋长为研究参数对仿方竹薄壁管耐撞特性进行了仿真分析。在此基础上,采用全因子试验设计方法来构建响应面模型,以比吸能和初始峰值载荷为目标函数,运用多目标粒子群优化算法进行优化求解并获得最优解的Pareto集。研究结果表明:仿方竹结构薄壁管有较好的耐撞性和稳定性,壁厚0.892 mm、肋长2.995 mm为仿方竹结构的最优解,此时初始峰值载荷和比吸能分别为10 k N和7.936598 k J/kg。研究结果对薄壁管的结构设计和尺寸优化具有重要意义。展开更多
To get the movement mode and driving mechanism similar to human shoulder joint,a six degrees of freedom(DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators(PMAs)was designed.Howev...To get the movement mode and driving mechanism similar to human shoulder joint,a six degrees of freedom(DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators(PMAs)was designed.However,the structural parameters of the shoulder joint will affect various performances of the mechanism.To obtain the optimal structure parameters,the particle swarm optimization(PSO) was used.Besides,the mathematical expressions of indexes of rotation ranges,maximum bearing torque,discrete dexterity and muscle shrinkage of the bionic shoulder joint were established respectively to represent its many-sided characteristics.And the multi-objective optimization problem was transformed into a single-objective optimization problem by using the weighted-sum method.The normalization method and adaptive-weight method were used to determine each optimization index's weight coefficient;then the particle swarm optimization was used to optimize the integrated objective function of the bionic shoulder joint and the optimal solution was obtained.Compared with the average optimization generations and the optimal target values of many experiments,using adaptive-weight method to adjust weights of integrated objective function is better than using normalization method,which validates superiority of the adaptive-weight method.展开更多
针对气动机械手动态特性强、特征状态难捕捉,导致稳定性控制误差较大的问题,提出一种基于仿生群智能优化径向基函数(Radial Basis Function Network,RBF)神经网络的气动机械手稳定运动控制方法。建立线性传递函数,计算气动回路中液压元...针对气动机械手动态特性强、特征状态难捕捉,导致稳定性控制误差较大的问题,提出一种基于仿生群智能优化径向基函数(Radial Basis Function Network,RBF)神经网络的气动机械手稳定运动控制方法。建立线性传递函数,计算气动回路中液压元件、气源装置、气压过滤装置、过滤器、调压阀以及压力计算器等元件间气动稳定关系,获取气动机械手回路状态。通过仿生群混合蛙跳算法智能优化RBF神经网络,根据机械手自由臂模型,建立坐标轴,计算机械臂各个关节角的自由度参数,根据机械手速度自由度、位移以及角度关系自由度设置比例-积分-微分(Proportion Integration Differentiation,PID)控制器,完成气动机械手稳定性控制输出。实验结果表明;该方法控制精准度高,在X轴、Y轴和Z轴方向上加速度曲线的波动性最小,具有良好的控制性能。展开更多
文摘薄壁金属管是发生碰撞时为安全性所设置的关键吸能构件。为了提高薄壁管结构的耐撞性,结合方管的易安装性和圆管的稳定性,基于方竹结构对薄壁管截面进行耐撞性分析和仿生优化设计。通过对方竹结构的原型分析,利用ABAQUS搭建了仿方竹结构薄壁管有限元分析模型,在对模型进行试验验证的基础上,以壁厚、肋长为研究参数对仿方竹薄壁管耐撞特性进行了仿真分析。在此基础上,采用全因子试验设计方法来构建响应面模型,以比吸能和初始峰值载荷为目标函数,运用多目标粒子群优化算法进行优化求解并获得最优解的Pareto集。研究结果表明:仿方竹结构薄壁管有较好的耐撞性和稳定性,壁厚0.892 mm、肋长2.995 mm为仿方竹结构的最优解,此时初始峰值载荷和比吸能分别为10 k N和7.936598 k J/kg。研究结果对薄壁管的结构设计和尺寸优化具有重要意义。
基金the National Natural Science Foundation of China(NO.51405229)the Natural Science Foundation of Jiangsu Province of China(Nos.BK20151470 and BK20130796)
文摘To get the movement mode and driving mechanism similar to human shoulder joint,a six degrees of freedom(DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators(PMAs)was designed.However,the structural parameters of the shoulder joint will affect various performances of the mechanism.To obtain the optimal structure parameters,the particle swarm optimization(PSO) was used.Besides,the mathematical expressions of indexes of rotation ranges,maximum bearing torque,discrete dexterity and muscle shrinkage of the bionic shoulder joint were established respectively to represent its many-sided characteristics.And the multi-objective optimization problem was transformed into a single-objective optimization problem by using the weighted-sum method.The normalization method and adaptive-weight method were used to determine each optimization index's weight coefficient;then the particle swarm optimization was used to optimize the integrated objective function of the bionic shoulder joint and the optimal solution was obtained.Compared with the average optimization generations and the optimal target values of many experiments,using adaptive-weight method to adjust weights of integrated objective function is better than using normalization method,which validates superiority of the adaptive-weight method.
