Structural Design and Optimization of Under-rank Coupling End Picker for Forging Robot
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摘要: 为了提高高温和振动环境中轮毂锻造机器人的夹持稳定性和安全性, 设计了一种轮毂锻造机器人欠秩耦合端拾器, 并进行了结构优化。首先, 将欠秩端拾器与弹簧杆件耦合, 进行了欠秩耦合端拾器的设计及其自适应抓取过程分析; 然后基于虚功原理, 建立了端拾器执行机构在自适应夹持状态下的接触力模型; 随后以接触力大小均衡性为要求建立结构参数优化模型, 并提出新自适应小世界算法及其优化流程; 最后利用自适应小世界优化算法完成了端拾器优化, 并将优化结果与经验法、Fmincon优化函数、遗传算法和基本小世界算法进行了比较。数值测试表明, 与其他4种算法相比, 自适应小世界算法的优化目标值最小, 且分别减少了97.4%、62.9%、52.3%和42.2%, 显示出小世界算法在欠秩耦合端拾器优化中的可行性和优越性; 而将所优化结构参数分别代入端拾器的接触力模型比较, 文中所优化端拾器不同接触点处接触力偏差最大值也最小, 且最大偏差分别减少了87.2%、82.6%、69.5%和42.1%, 满足了锻造机器人端拾器夹持时的接触力均衡性要求。Abstract: In order to improve the stability and safety of the forging parts clamping of the hub forging robot in the high temperature and vibration environments, an under-rank coupling end picker was designed and optimized. Firstly, the under-rank coupling end picker was designed by coupling the under-rank end picker and the spring rod and its adaptive grasping process was analyzed. Then the contact force model for the end picker actuator was established in terms of the principle of virtual work in the adaptive clamping state. Subsequently, the structural parameter optimization model was established with the requirement of the balance of the contact force, and a new adaptive small world algorithm (ASWA) and its optimization process were proposed. Finally, the end picker was optimized via an adaptive small world optimization algorithm, and the optimization results was compared with the empirical method, Fmincon optimization function, genetic algorithm and basic small world algorithm. Numerical tests show that comparing with the other four algorithms, the end picker optimization target value of the ASWA is the smallest, and reduced by 97.4%, 62.9%, 52.3% and 42.2% respectively, which shows that the small-world algorithm is feasibility and superiority in the optimization of under-rank coupling end pickup; furthermore, substituting the optimized structural parameters into the contact force model of the end picker, it shows that the maximum deviation of the contact force at different contact points is also the smallest, and the maximum deviation is reduced by 87.2%, 82.6%, 69.5% and 42.1% respectively, which meets the requirements for the balance of the contact force in the clamping of picker.
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Key words:
- under-rank /
- end picker /
- wheel hub /
- forging robot /
- small world algorithm
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表 1 5种算法的端拾器优化对比
算法 minf(X) σmax/ % h1/ mm h2/ mm h3/ mm a2/ mm a3/ mm a4/ mm a5/ mm β1/ rad β2/ rad β3/ rad γ1/ rad γ2/ rad α1/ rad φ2/ rad 经验法 5.453 6× 10-2 48.4 55 35 25 70 60 50 40 1.5 1.5 0.6 0.6 1.5 0.8 1.2 FOF 平均 4.313 3× 10-3 - - - - - - - - - - - - - - - 最优 3.7847× 10-3 35.6 68.824 51.833 65.970 37.141 11.178 59.341 1.388 39.742 0.876 0.981 0.764 0.827 0.683 1.279 GA 平均 3.3153× 10-3 - - - - - - - - - - - - - - - 最优 2.946 7× 10-3 20.3 70.322 53.655 76.571 57.067 14.792 60.960 1.048 59.651 0.731 1.239 0.768 0.866 0.778 1.531 SWA 平均 2.7324× 10-3 - - - - - - - - - - - - - - - 最优 2.429 4× 10-3 10.7 65.266 48.471 57.502 37.975 10.812 60.944 1.291 56.515 0.418 1.098 0.727 0.996 0.554 1.387 ASWA 平均 1.620 4× 10-3 - - - - - - - - - - - - - - - 最优 1.4042× 10-3 6.2 54.991 53.957 78.054 45.861 9.959 78.592 1.242 54.601 0.776 1.079 0.885 1.249 0.3678 1.211 
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