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工程设计学报
Chin J Eng Design  2023, Vol. 30 Issue (4): 503-511    DOI: 10.3785/j.issn.1006-754X.2023.00.052
Mechanical Optimization Design     
Optimization design of acceleration and deceleration curve of winding machine with large moment of inertia
Fangjian DOU1(),Qingying QIU1(),Cheng GUAN1,Jinjie SHAO1,Haifeng WU2
1.School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
2.The Eighth Research Institute, China National Nuclear Corporation, Shanghai 201800, China
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Abstract  

Aiming at the problems of unstable operation and easy failure of transmission parts during acceleration and deceleration of carbon fiber winding machine with large moment of inertia, an optimization scheme of spindle operation curve based on improved Sigmoid acceleration and deceleration curve was proposed. Firstly, the quintic polynomial was used to compensate the mutation of the traditional Sigmoid acceleration and deceleration curve by constraining the velocity, acceleration and jerk of the starting point, connecting point and ending point of the curve. Then, the mathematical models of load torque, motor output power, strength and stiffness of spindle and number of winding coils were established based on the velocity and acceleration functions of the improved curve. The multi-objective optimization for the curve was carried out with the operating time of each stage as the design variables and the maximum motor output power and total operating time as the optimization objectives. Under the constraints of the number of winding coils, strength and stiffness of transmission parts and so on, the non-dominated solution set was solved by the multi-objective genetic algorithm NSGA-Ⅱ(non-dominated sorting genetic algorithm-Ⅱ), and the optimal solution was selected by the proportion selection function. Finally, through AMESim-ADAMS co-simulation, the operation effects of winding machine before and after acceleration and deceleration curve optimization were compared. The results showed that the total operating time, maximum acceleration, maximum load torque and maximum output power of the optimized winding machine were reduced by 41.7%, 75.8%, 75.5% and 72.8%, and the spindle operation curve was smoother, which verified the feasibility of the optimization scheme. The research results provide a new solution for the problem of unstable operation or transmission parts failure of rotating equipment with large moment of inertia.

Key words： large moment of inertia      winding machine      acceleration and deceleration curve      multi-objective optimization      genetic algorithm     
Received: 29 December 2022      Published: 04 September 2023
CLC:  TH 123  
Corresponding Authors: Qingying QIU     E-mail: 2397351750@qq.com;medesign@zju.edu.cn
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Fangjian DOU
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Jinjie SHAO
Haifeng WU
Cite this article:

Fangjian DOU,Qingying QIU,Cheng GUAN,Jinjie SHAO,Haifeng WU. Optimization design of acceleration and deceleration curve of winding machine with large moment of inertia. Chin J Eng Design, 2023, 30(4): 503-511.

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https://www.zjujournals.com/gcsjxb/10.3785/j.issn.1006-754X.2023.00.052     OR     https://www.zjujournals.com/gcsjxb/Y2023/V30/I4/503


大转动惯量缠绕机加减速曲线优化设计

针对大转动惯量碳纤维缠绕机的加速和减速阶段运行不平稳、传动件易失效破坏等问题，提出了一种基于改进型Sigmoid加减速曲线的主轴运行曲线优化方案。首先，利用五次多项式对传统Sigmoid加减速曲线的跃变处进行补偿，以约束曲线起始点、衔接点、终止点的速度、加速度和急动度（加加速度）。然后，基于改进曲线的速度与加速度函数建立缠绕机的负载扭矩、电机输出功率、主轴强度与刚度以及缠绕圈数的数学模型，并以各阶段运行时长为设计变量、以电机最大输出功率最小和总运行时长最短为优化目标对曲线进行多目标优化，根据缠绕圈数、传动件强度与刚度等的约束条件，利用多目标遗传算法NSGA-Ⅱ（non-dominated sorting genetic algorithm-Ⅱ，非支配排序遗传算法-Ⅱ）求解模型的非支配解集，并利用比重选取函数选择最优解。最后，通过AMESim-ADAMS联合仿真对比加减速曲线优化前后缠绕机的运行效果。结果表明：优化后缠绕机的总运行时长、最大加速度、最大负载扭矩和最大输出功率分别降低了41.7%，75.8%，75.5%和72.8%，且主轴的运行曲线更加平滑，验证了优化方案的可行性。研究结果为大转动惯量旋转设备的运行不平稳或传动件失效问题提供了一种新的解决思路。


关键词： 大转动惯量,  缠绕机,  加减速曲线,  多目标优化,  遗传算法 
Fig.1 Structure diagram of carbon fiber winding machine
Fig.2 Traditional Sigmoid velocity curve
Fig.3 Traditional Sigmoid acceleration curve
Fig.4 Improved Sigmoid velocity curve
Fig.5 Improved Sigmoid acceleration curve
Fig.6 Multi-objective optimization model relationships for acceleration and deceleration curve of winding machine
参数量值参数量值
Jm1 129.14 kg·m2Ssσ18.415
η10.94τs313.2 MPa
η20.99Wτ8.284×10-5 m3
vm2.094 4 rad/sG8.1×104 MPa
T23 sIP1.868×10-6 m3
M1 214.56 N·mnz2.3圈
W4.142×10-5 m3[σ-1]70 MPa
Sσ3.780 5S1.5
Kτ3.028 7Ss1.6
?τ0.05[φ]1.5°
τ-1200 MPaML6 300 N·m
WT8.284×10-5 m3
Table 1 Main parameters of winding machine
Fig.7 Pareto frontier of multi-objective optimization model for acceleration and deceleration curve of winding machine
Fig.8 AMESim-ADAMS co-simulation of winding machine
Fig.9 Comparison of operation effect of winding machine before and after optimization
优化前后总运行时长Tz/s最大加速度amax/(rad/s2)最大负载扭矩MT max/(N·m)最大输出功率Pmax/kW
改进率/%41.775.875.572.8
优化前17.988.5529 650.0111.810
优化后10.482.0672 366.783.211
Table 2 Comparison of operation performance of winding machine before and after optimization
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