Please wait a minute...
Chinese Journal of Engineering Design  2020, Vol. 27 Issue (1): 67-75    DOI: 10.3785/j.issn.1006-754X.2020.00.006
Optimization Design     
Multi-objective optimization design of deployable mechanism of scissor folding bridge based on GA-NLP
ZHANG Shuai1,2, HAN Jun3, TU Qun-zhang1, YANG Xiao-qiang1, YANG Xuan1
1.College of Field Engineering, Army Engineering University of PLA,Nanjing 21007,China
2.Professional Education and Field Training Base, Army Engineering University of PLA,Xuzhou 221004,China
3.The Fifth Research Institute, Army Academy of PLA,Wuxi 214035,China
Download: HTML     PDF(3363KB)
Export: BibTeX | EndNote (RIS)      

Abstract  Aiming at the optimization design of deployable mechanism of a new type of scissor folding bridge, the kinematics and statics models of the deployable mechanism were established at first. Then, the key hinge position of the deployable mechanism and the angle between the side bridge section and the vertical direction were selected as the variables for optimization design. The spatial position of the deployable mechanism was selected as the main constraint condition. Meanwhile, the optimization target was defined as minimizing the peak force of deployable bridge cylinder, linkage and the key hinge points. After the multi-optimization targets were normalized and weighted, the multi-objective optimization analysis model of the deployable mechanism was constructed. The genetic algorithm and nonlinear programming (GA-NLP) hybrid approach was used to solve the multi-objective optimization model. The correctness of the multi-objective optimization model of the deployable mechanism was verified by ADAMS software. The research results showed that the peak pulling force and pushing force of deployment mechanism cylinder decreased by 57.9% and 25.3% respectively. The peak pulling force and pressure of linkage decreased by 26.1% and 55.2% respectively, and the peak force of two key hinge points of deployable mechanism decreased by 23.5% and 26.8% respectively. The research results can provide a theoretical basis for the optimization design of the deployable mechanism.

Received: 10 April 2019      Published: 28 February 2020
CLC:  TH 122  
  TP 391.9  
Cite this article:

ZHANG Shuai, HAN Jun, TU Qun-zhang, YANG Xiao-qiang, YANG Xuan. Multi-objective optimization design of deployable mechanism of scissor folding bridge based on GA-NLP. Chinese Journal of Engineering Design, 2020, 27(1): 67-75.

URL:

https://www.zjujournals.com/gcsjxb/10.3785/j.issn.1006-754X.2020.00.006     OR     https://www.zjujournals.com/gcsjxb/Y2020/V27/I1/67


基于GA-NLP的剪刀式折叠桥梁展桥机构多目标优化设计

针对新型剪刀式折叠桥梁展桥机构的优化设计问题,首先建立了展桥机构的运动学和静力学模型,然后以展桥机构关键铰点位置和岸桥节与竖直方向所成夹角为优化设计变量,以展桥机构的空间位置为主要约束条件,以展桥油缸、连杆、关键铰点受力峰值最小为优化目标,通过正规化和加权处理构造了展桥机构多目标优化分析模型,并采用遗传算法(genetic algorithm, GA)和非线性规划(nonlinear programming, NLP)混合算法对该优化分析模型进行求解。最后,利用ADAMS(automatic dynamic analysis of mechanical systems,机械系统动力学自动分析)软件验证了展桥机构多目标优化分析模型的正确性。结果表明,优化后展桥油缸承载的拉力与推力峰值分别减小了57.9%和25.3%,连杆承载的拉力与压力峰值分别减小了26.1%和55.2%,展桥机构2个关键铰点受力峰值分别减小了23.5%和26.8%。研究结果可为展桥机构的改进设计提供理论依据。
[1] Jia-ning ZHANG,Ming-lu ZHANG,Man-hong LI,Tan ZHANG. Structural design and stiffness optimization of mechanical arm with super large telescopic ratio for ash silo cleaning[J]. Chinese Journal of Engineering Design, 2022, 29(4): 430-437.
[2] Chen WANG,Bo GAO,Xu YANG. Lightweight design of Stewart type six-axis force sensor[J]. Chinese Journal of Engineering Design, 2022, 29(4): 419-429.
[3] Jing-liang WANG,Tian-cheng ZHU,Long-biao ZHU,Fei-yun XU. Research on variable density topology optimization method for continuum structure[J]. Chinese Journal of Engineering Design, 2022, 29(3): 279-285.
[4] Guang-ming SUN,Yi-miao WANG,Qian WAN,Kun GONG,Wen-jin WANG,Jian ZHAO. Optimization design of precision machine tool bed considering assembly deformation[J]. Chinese Journal of Engineering Design, 2022, 29(3): 318-326.
[5] Hong-bin RUI,Lu-lu LI,Wei CAO,Tian-ci WANG,Kai-wen DUAN,Ying-hui WU. Gait planning and obstacle-surmounting performance analysis of wheel-track-leg composite bionic robot[J]. Chinese Journal of Engineering Design, 2022, 29(2): 133-142.
[6] Hong-yu LIAO,Meng-yang DENG,Min ZHOU,Liang-xi XIE,Jun-fu YAO. Lightweight design of automatic plastering machine based on wire rope transmission[J]. Chinese Journal of Engineering Design, 2022, 29(2): 196-201.
[7] Chuan-long XIN,Rong ZHENG,Fu-lin REN,Hong-guang LIANG. Suspension balance analysis and counterweight optimization design of AUV docking device[J]. Chinese Journal of Engineering Design, 2022, 29(2): 176-186.
[8] Yun-jie XU,Yu SHEN,Fei HU,Liang-quan JIA,Heng-nian QI. Design of vigor detection device for batch seeds based on TDLAS[J]. Chinese Journal of Engineering Design, 2022, 29(2): 231-236.
[9] TAO Xiao-dong, GUO An-fu, LI Hui, HAN Wei, LI Wan-cai, LI Tao. Performance analysis and optimization of disc ditcher based on sensitivity analysis[J]. Chinese Journal of Engineering Design, 2022, 29(1): 59-65.
[10] FAN Xiao-yue, LIU Qi, GUAN Wei, ZHU Yun, CHEN Su-lin, SHEN Bin. Simulation and experimental research on thermal effect of electromagnetic micro hammer peening mechanism[J]. Chinese Journal of Engineering Design, 2022, 29(1): 66-73.
[11] WANG Bi-hai, ZHANG Jian, CHEN Yong-liang, PENG Qing-jin, GU Pei-hua. Intelligent decision for adaptive design of shield screw conveyor[J]. Chinese Journal of Engineering Design, 2022, 29(1): 1-9.
[12] WANG Hong-gang, KANG Cun-feng, CHEN Kang-wen, JI Yuan-long, PU Qiu-ran, ZHANG Lei-yu. Study on effect of slider rocker mechanism on rehabilitation of triceps surae[J]. Chinese Journal of Engineering Design, 2021, 28(6): 687-693.
[13] NI Wei-yu, ZHANG Heng, YAO Sheng-wei. Lightweight design of automobile seat frame based on multiple working conditions[J]. Chinese Journal of Engineering Design, 2021, 28(6): 729-736.
[14] NI Zi-jian, LI Wen-qiang, TANG Zhong. Ontology semantic mining and functional semantic retrieval method based on network representation learning[J]. Chinese Journal of Engineering Design, 2021, 28(5): 539-547.
[15] ZHENG Yu-chen, JU Feng, WANG Dan, SUN Jing-bin, WANG Ya-ming, CHEN Bai. Design and control research of aeroengine blade detection robot[J]. Chinese Journal of Engineering Design, 2021, 28(5): 625-632.