高速重载码垛机器人动态特性分析及结构优化研究

发布时间：2018-04-16 06:29

本文选题：高速重载 + 柔性　；参考：《哈尔滨工业大学》2015年硕士论文

【摘要】：随着高速重载码垛机器人在汽车、冶金、物流等行业的广泛应用,自动化生产线对机器人的搬运速度、负载能力、加速度和定位精度提出了更高的要求。针对高速重载码垛机器人高速、高精度、大负载的工作特性,仅在运动学层面上进行结构设计还不够,有必要依据动静力学性能分析,对机器人本体进行重点面向动态特性的结构优化研究。因此,本文从高速重载码垛机器人的工作特性出发,提出一种基于动态特性分析的高速重载码垛机器人优化设计方法。首先,基于D-H参数法和第二类拉格朗日方程对高速重载码垛机器人进行运动学和动力学建模,推导出运动学正解及雅克比矩阵,结合减速机简化模型建立了刚柔耦合动力学模型。利用ADAMS分析软件,建立了机器人虚拟模型,进行了动力学仿真,验证了关节柔性对机器人性能的影响以及动力学方程的正确性。其次,借助有限元仿真分析,对码垛机器人的三个典型位姿进行了模态分析。结果显示,最低阶固有频率主要是由于大臂的关节柔性引起的摇摆振动,小臂弯曲和大臂扭转也会对系统产生较大影响。接着通过多点激励单点拾取的模态分析方案,借助BOBCAT动态测试系统,进行了典型位姿下的整体动态实验。根据模态分析结果,提出了采用有限元分析软件优化大小臂杆件柔性,理论建模优化关节柔性指标的码垛机器人整体结构优化方法。最后,考虑杆件柔性,利用有限元分析软件对大小臂进行结构优化。然后,针对关节柔性对系统带来的影响,确定了固有频率,静刚度和速度特性作为优化目标,建立了关节柔性多目标优化模型。根据模态分析理论,采用振型叠加法进行了码垛机器人的振动模态理论分析研究。通过大小臂简化处理,以及固有频率相对灵敏度分析,确定了优化变量。通过优化目标的性能谱图分析,得到了优化目标间的耦合性关系。结合码垛机器人其他具体工作需求,确定以工作空间、最大加速能力和大小臂刚度作为约束条件。最后,进行了多目标优化模型的求解和优化结果分析。针对NSGA-II存在的缺陷,对交叉算子和拥挤度排序进行了改进,并通过典型测试函数和性能评价指标,验证了改进算法的有效性。通过改进NSGA-II算法进行优化模型的求解,根据实际需求选取了最优解。优化结果分析表明,各个性能都得到了一定程度的提升,并通过仿真分析验证了结构优化的有效性。
[Abstract]:With the wide application of high-speed and heavy-duty palletizing robot in automobile, metallurgy, logistics and other industries, the automatic production line has put forward higher requirements for the robot's handling speed, load capacity, acceleration and positioning accuracy.In view of the high speed, high precision and large load working characteristics of high speed and heavy load palletizing robot, it is not enough to design the structure on the kinematics level, so it is necessary to analyze the dynamic and static properties of the palletizing robot.The dynamic characteristic oriented structure optimization of robot ontology is studied.Therefore, based on the working characteristics of high speed and heavy load palletizing robot, an optimal design method of high speed heavy load palletizing robot based on dynamic characteristic analysis is proposed in this paper.Firstly, based on D-H parameter method and Lagrangian equation of the second kind, kinematics and dynamics of high speed and heavy load palletizing robot are modeled, and the forward kinematics solution and Jacobian matrix are derived.The rigid-flexible coupling dynamic model is established with the simplified model of reducer.The virtual model of robot is established by using ADAMS software, and the dynamic simulation is carried out, which verifies the effect of joint flexibility on robot performance and the correctness of dynamic equation.Secondly, the modal analysis of three typical postures of palletizing robot is carried out by means of finite element simulation.The results show that the lowest natural frequency is mainly due to the swinging vibration caused by the joint flexibility of the arm, and the bending of the forearm and the torsion of the arm will also have a great influence on the system.Then, through the modal analysis scheme of multi-point excitation single point pickup, the whole dynamic experiment under typical position and pose is carried out with the help of BOBCAT dynamic test system.Based on the modal analysis results, a new optimization method for the overall structure of a stacking robot is proposed, which uses finite element analysis software to optimize the flexibility of the large and small arms and the theoretical model to optimize the flexibility index of the joints.Finally, considering the flexibility of the bar, the finite element analysis software is used to optimize the structure of the upper arm.Then, aiming at the impact of joint flexibility on the system, the natural frequency, static stiffness and velocity characteristics are determined as the optimization objectives, and a multi-objective optimization model of joint flexibility is established.According to modal analysis theory, vibration modal analysis of stacking robot is carried out by mode superposition method.The optimization variables are determined by the simplified treatment of the upper arm and the relative sensitivity analysis of the natural frequency.The coupling relationship between the optimized targets is obtained by analyzing the performance spectrum of the optimized targets.According to the other requirements of palletizing robot, the workspace, the maximum acceleration ability and the stiffness of the upper arm are chosen as the constraint conditions.Finally, the multi-objective optimization model is solved and the optimization results are analyzed.Aiming at the defects of NSGA-II, the crossover operator and congestion ranking are improved, and the effectiveness of the improved algorithm is verified by the typical test function and performance evaluation index.Through the improved NSGA-II algorithm to solve the optimization model, the optimal solution is selected according to the actual demand.The results of optimization show that each performance has been improved to a certain extent, and the effectiveness of structural optimization is verified by simulation analysis.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP242

【参考文献】