Please wait a minute...
工程设计学报  2024, Vol. 31 Issue (5): 592-602    DOI: 10.3785/j.issn.1006-754X.2024.03.225
优化设计     
爬壁机器人磁吸附模块设计分析与结构参数优化
杨培(),张明路,孙凌宇()
河北工业大学 机械工程学院,天津 300130
Design analysis and structural parameter optimization for magnetic adsorption module of wall-climbing robot
Pei YANG(),Minglu ZHANG,Lingyu SUN()
School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
 全文: PDF(4025 KB)   HTML
摘要:

作为磁吸附式爬壁机器人的关键部件,磁吸附模块的结构通常会影响机器人的整体质量及吸附稳定性。针对磁吸附模块磁路耦合关系复杂、优化设计困难等问题,结合虚拟仿真技术、代理模型和蜣螂优化算法提出了一种磁吸附模块结构优化方法,以提高其磁力计算和优化设计过程的效率。首先,介绍了爬壁机器人的结构设计方案,并通过对现有的Halbach阵列磁路模式进行仿真分析,确定了三磁路模式具有相对较高的吸附效率;同时,基于初设参数对磁吸附模块磁力仿真模型进行了实验验证,为后续代理模型的建立奠定了基础。然后,建立了以机器人吸附稳定性和结构参数为约束、以磁吸附模块轻量化为目标的优化模型。采用最优拉丁超立方设计、ANSYS参数化建模以及代理模型技术建立了磁吸附模块磁力与结构参数之间的四阶响应面模型,并对其可信度进行了验证。利用蜣螂优化算法对磁吸附模块的结构参数优化模型进行了求解。结果表明,所建立的代理模型的预测误差很小,能够较好地表征磁吸附模块磁力与结构参数之间的关系;优化后磁吸附模块的质量减小了12.7%。最后,通过机器人负载实验验证了优化过程的正确性。研究结果可为其他磁吸附式机器人的磁力分析与结构优化提供参考。

关键词: 爬壁机器人磁吸附模块代理模型参数优化磁路仿真分析    
Abstract:

As a vital component of the magnetic adsorption wall-climbing robot, the structure of the magnetic adsorption module usually affects the overall mass and adsorption stability of the robot. Aiming at the problems of complex magnetic circuit coupling relationship and complicated optimization design of magnetic adsorption modules, a magnetic adsorption module structure optimization method is proposed by combining virtual simulation technology, surrogate model and dung beetle optimization algorithm to improve the efficiency of magnetic force calculation and optimization design process. Firstly, the structure design scheme for the wall-climbing robot was introduced, and through the simulation analysis of the existing Halbach array magnetic circuit modes, it was determined that the three-magnetic circuit mode had relatively high adsorption efficiency. At the same time, the magnetic force simulation model of the magnetic adsorption module was experimentally verified based on the initial parameters, which laid the foundation for establishing subsequent surrogate models. Then, an optimization model with the robot's adsorption stability and structural parameters as constraints and the lightweight of the magnetic adsorption module as objective was established. A fourth-order response surface model between the magnetic force and the structural parameters of the magnetic adsorption module was established by the optimal Latin hypercube design, ANSYS parametric modeling and surrogate model technology, and its credibility was verified. The structural parameter optimization model of the magnetic adsorption module was solved by using the dung beetle optimization algorithm. The results showed that the prediction error of the established surrogate model was tiny, and the relationship between the magnetic force and the structural parameters of the magnetic adsorption module could be well expressed. After optimization, the mass of the magnetic adsorption module was reduced by 12.7%. Finally, the correctness of the optimization process was verified through robot load experiments. The research results can provide reference for the magnetic force analysis and structure optimization of other magnetic adsorption robots.

Key words: wall-climbing robot    magnetic adsorption module    surrogate model    parameter optimization    magnetic circuit simulation
收稿日期: 2023-12-26 出版日期: 2024-10-30
CLC:  TP 242.2  
基金资助: 国家重点研发计划资助项目(2018YFB1309400);慧眼行动计划资助项目(62602010243);河北工业大学学科交叉方向研究生培养资助项目(HEBUT-Y-XKJC-2021119)
通讯作者: 孙凌宇     E-mail: yang_p1993@163.com;sunly@hebut.edu.cn
作者简介: 杨 培(1993—),男,博士生,从事特种机器人技术及应用等研究,E-mail: yang_p1993@163.com,https://orcid.org/0009-0000-6910-0358
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
杨培
张明路
孙凌宇

引用本文:

杨培,张明路,孙凌宇. 爬壁机器人磁吸附模块设计分析与结构参数优化[J]. 工程设计学报, 2024, 31(5): 592-602.

Pei YANG,Minglu ZHANG,Lingyu SUN. Design analysis and structural parameter optimization for magnetic adsorption module of wall-climbing robot[J]. Chinese Journal of Engineering Design, 2024, 31(5): 592-602.

链接本文:

https://www.zjujournals.com/gcsjxb/CN/10.3785/j.issn.1006-754X.2024.03.225        https://www.zjujournals.com/gcsjxb/CN/Y2024/V31/I5/592

图1  爬壁机器人整体结构
图2  4种磁路模式的结构
图3  不同磁路模式下磁力随气隙距离的变化情况
图4  三磁路磁吸附模块结构示意
图5  磁吸附模块结构参数优化策略
图6  不同壁面厚度下磁力的变化情况
设计参数初始值取值范围
最小值最大值
a8512
b16529
c352637
d221230
e114.521.5
t101010
g101010
表1  磁吸附模块各设计参数的取值范围 (mm)
图7  爬壁机器人受力分析
图8  抵抗3种失稳情况时所需的最小磁力
图9  磁吸附模块磁力测试实验平台
图10  磁吸附模块磁力的仿真值与实测值对比
图11  不同试验设计方法的采样效果
样本点a/mmb/mmc/mmd/mme/mmFX)/N
15.35421.4829.8921.4513.26128.570
25.99022.9428.4412.9114.4669.073
38.8897.4236.2221.6418.2487.366
48.04015.1836.1114.557.9365.284
510.72722.7035.8928.5513.43272.450
66.83827.5533.3326.7311.71213.010
77.19216.6435.7817.2720.81142.230
89.0305.7334.6716.5511.3737.808
98.74724.3928.6712.738.9649.399
108.32320.5231.2221.097.59109.780
1111.22220.2736.7816.739.65107.380
126.27321.9734.2226.364.50137.260
1311.36420.0326.5615.0912.5766.402
145.42425.1233.1115.6418.58135.950
1511.0108.1527.4424.737.7666.603
168.18213.4826.7813.0912.2342.979
176.13113.9736.5619.8213.09126.730
186.7685.9729.5614.3616.3528.872
1910.0205.2431.5623.4512.9150.487
2011.64619.7932.6714.1817.3899.943
7911.71721.7327.0024.5512.74141.920
805.63624.8835.4419.098.96124.080
816.41412.2726.1120.0015.4977.611
8211.43410.5830.0022.5519.27104.780
8311.50522.4531.6714.738.4567.949
845.7076.7033.8916.368.2839.014
8510.4448.8836.6723.649.82105.650
865.28313.2427.5625.459.3188.687
878.46517.8526.0025.2710.17113.340
889.24217.1234.4421.2713.94153.140
8911.78817.8534.1124.187.42147.230
9011.9299.3634.5618.7315.8384.310
9111.15211.3034.8927.6417.21172.770
929.4559.8532.4415.8220.3069.653
935.21217.3632.8914.0011.5471.916
9410.79819.0628.8926.185.02119.520
9511.29311.7933.7812.009.9942.234
969.5255.4829.4415.458.7924.149
977.0515.0035.2224.9111.8858.269
9810.86914.4530.5628.9112.06167.910
9911.08110.0929.3312.3615.3240.109
1006.98024.6426.6718.9119.61126.210
表2  构建磁力代理模型的部分样本点及对应的磁力仿真值
代理模型R2ERMS
2-RSM0.987 30.025 46
4-RSM0.994 40.016 96
表3  代理模型的精度评价指标
图12  不同代理模型的预测效果对比
组别结构参数/mm磁力仿真值/N磁力预测值/N相对误差/%
abcde2-RSM4-RSM2-RSM4-RSM
初始816352211142.92134.53138.445.873.13
测试171329181376.9374.0278.823.782.46
测试2917322114135.27129.75133.104.081.60
测试310.5233525.518256.96245.66248.844.403.16
测试41229373021398.49380.92393.514.411.25
表4  不同结构参数组合下磁力的相对误差对比
图13  基于DBO算法的磁吸附模块结构参数优化求解流程
参数数值
种群数量/个90
迭代数/次1 000
各子种群数量(滚球∶产卵∶觅食∶偷窃)6∶6∶7∶11
滚球蜣螂缺陷系数0.1
滚球蜣螂常值0.3
滚球、跳舞行为概率0.5
觅食蜣螂常值0.5
表5  DBO算法的主要参数
图14  基于2-RSM和4-RSM的优化求解迭代过程
结构参数与性能参数初始值优化值
2-RSM4-RSM(取整
a/mm855(5)
b/mm1611.8511.803 9(11.8)
c/mm353737(37)
d/mm2230.0025.568(25.6)
e/mm114.9813.8145(13.8)
mX)/g353.43309.41308.49(308.66)
FX)/N143.00143.00(143.12)
表6  磁吸附模块结构参数优化结果
图15  爬壁机器人负载实验现场
1 陈咏华, 孙振国, 张文, 等. 爬壁机器人焊缝高效修形技术研究[J]. 机械工程学报, 2023, 59(9): 12-19. doi:10.3901/jme.2023.09.012
CHEN Y H, SUN Z G, ZHANG W, et al. Research on high efficiency weld modification technology for wall-climbing robot[J]. Journal of Mechanical Engineering, 2023, 59(9): 12-19.
doi: 10.3901/jme.2023.09.012
2 刘志辉, 蔡伟, 付兴伟, 等. 一种滚动密封爬壁机器人失效分析[J]. 中国机械工程, 2022, 33(22): 2755-2763, 2771.
LIU Z H, CAI W, FU X W, et al. Failure analysis of a rolling sealed wall climbing robots[J]. China Mechanical Engineering, 2022, 33(22): 2755-2763, 2771.
3 王洋, 张小俊, 张明路, 等. 可自适应变曲率立面的分体柔性爬壁机器人设计与分析[J]. 机械工程学报, 2021, 57(3): 49-58. doi:10.3901/jme.2021.03.049
WANG Y, ZHANG X J, ZHANG M L, et al. Design and analysis of split-flexible wall-climbing robot with adaptive variable curvature facade[J]. Journal of Mechanical Engineering, 2021, 57(3): 49-58.
doi: 10.3901/jme.2021.03.049
4 姜泽, 王珉, 赵哲, 等. 爬壁机器人发展现状与关键技术研究综述[J]. 包装工程, 2023, 44(12): 29-38, 117, 8.
JIANG Z, WANG M, ZHAO Z, et al. Review on development status and key technologies of wall-climbing robots[J]. Packaging Engineering, 2023, 44(12): 29-38, 117, 8.
5 马吉良, 彭军, 郭艳婕, 等. 爬壁机器人研究现状及发展趋势[J]. 机械工程学报, 2023, 59(5): 11-28. doi:10.3901/jme.2023.05.011
MA J L, PENG J, GUO Y J, et al. Research status and development trend of wall climbing robot[J]. Journal of Mechanical Engineering, 2023, 59(5): 11-28.
doi: 10.3901/jme.2023.05.011
6 周依霖, 张华, 叶艳辉, 等. 永磁吸附履带式爬壁机器人转向动力特性分析[J]. 机械设计, 2017, 34(2): 56-61.
ZHOU Y L, ZHANG H, YE Y H, et al. Steering dynamic characteristics analysis of permanent magnetic tracked wall-climbing robot[J]. Journal of Machine Design, 2017, 34(2): 56-61.
7 LU X R, GUO D H, CHEN Y. Design and optimization of the magnetic adsorption mechanism of a pipeline-climbing robot[J]. Journal of Mechanical Science and Technology, 2021, 35(11): 5161-5171.
8 张栋, 杨培, 黄哲轩, 等. 爬壁机器人悬摆式磁吸附机构的设计与优化[J]. 工程设计学报, 2023, 30(3): 334-341.
ZHANG D, YANG P, HUANG Z X, et al. Design and optimization of pendulous magnetic adsorption mechanism for wall-climbing robots[J]. Chinese Journal of Engineering Design, 2023, 30(3): 334-341.
9 SAHBEL A, ABBAS A, SATTAR T. Experimental and numerical optimization of magnetic adhesion force for wall climbing robot applications[J]. International Journal of Mechanical Engineering and Robotics Research, 2019, 8(1): 18-24.
10 HALBACH K. Strong rare earth cobalt quadrupoles[J]. IEEE Transactions on Nuclear Science, 1979, 26(3): 3882-3884.
11 钟道方, 田颖, 张明路. 轮腿式爬壁机器人的永磁吸附装置设计与优化[J]. 工程设计学报, 2022, 29(1): 41-50.
ZHONG D F, TIAN Y, ZHANG M L. Design and optimization of permanent magnet adsorption device for wheel-legged wall-climbing robot[J]. Chinese Journal of Engineering Design, 2022, 29(1): 41-50.
12 潘柏松, 张晋, 魏凯, 等. 基于Halbach阵列爬壁机器人永磁轮吸附单元的设计与优化[J]. 浙江工业大学学报, 2015, 43(4): 393-397, 474. doi:10.3969/j.issn.1006-4303.2015.04.009
PAN B S, ZHANG J, WEI K, et al. The optimization of a novel permanent-magnetic wheel adsorption unit for wall-climbing robot based on Halbach array[J]. Journal of Zhejiang University of Technology, 2015, 43(4): 393-397, 474.
doi: 10.3969/j.issn.1006-4303.2015.04.009
13 陈勇. Halbach阵列机器人磁吸附单元理论分析与实验研究[D]. 南京: 南京理工大学, 2013.
CHEN Y. Theoretical and experiment research on magnetic adhesion device for wall-climbing robot based on Halbach array[D]. Nanjing: Nanjing University of Science and Technology, 2013.
14 JIAO S L, ZHANG X J, ZHANG X, et al. Magnetic circuit analysis of Halbach array and improvement of permanent magnetic adsorption device for wall-climbing robot[J]. Symmetry, 2022, 14(2): 429.
15 赵智浩, 陶友瑞, 裴佳星, 等. 履带式爬壁机器人磁吸附单元的参数分析与优化[J]. 机械强度, 2023, 45(3): 626-632.
ZHAO Z H, TAO Y R, PEI J X, et al. Parameter analysis and optimization of magnetic adsorption unit for crawler wall-climbing robot[J]. Journal of Mechanical Strength, 2023, 45(3): 626-632.
16 ZHAO Z H, TAO Y R, WANG J, et al. The multi-objective optimization design for the magnetic adsorption unit of wall-climbing robot[J]. Journal of Mechanical Science and Technology, 2022, 36(1): 305-316.
17 孙玲. 除锈爬壁机器人壁面行走控制技术研究[D]. 大连: 大连海事大学, 2015.
SUN L. Research on wall travelling control for ship rust removal wall climbing robot[D]. Dalian: Dalian Maritime University, 2015.
18 黄哲轩. 石化储罐壁面检测爬壁机器人设计及其特性研究[D]. 天津: 河北工业大学, 2018.
HUANG Z X. Wall-climbing robot design and property study based on surface testing of petrochemical tank[D]. Tianjin: Hebei University of Technology, 2018.
19 PALAR P S, SHIMOYAMA K. On efficient global optimization via universal Kriging surrogate models[J]. Structural and Multidisciplinary Optimization, 2018, 57: 2377-2397.
20 KEANE A J, VOUTCHKOV I I. Robust design optimization using surrogate models[J]. Journal of Computational Design and Engineering, 2020, 7(1): 44-55.
21 张扬. 多参数非线性系统全局敏感性分析与动态代理模型研究[D]. 长沙: 湖南大学, 2014.
ZHANG Y. The study on global sensitivity analysis and dynamic metamodel of multiple-parameters nonlinear system[D]. Changsha: Hunan University, 2014.
[1] 张栋,杨培,黄哲轩,孙凌宇,张明路. 爬壁机器人悬摆式磁吸附机构的设计与优化[J]. 工程设计学报, 2023, 30(3): 334-341.
[2] 张鹏程,牛建业,刘承磊,宋井科,王立鹏,张建军. 牵引式下肢康复机器人机构参数优化及轨迹规划[J]. 工程设计学报, 2022, 29(6): 695-704.
[3] 张文豪,班传文,李松梅. 基于离散元法的双组份复合涂料搅拌螺杆参数优化[J]. 工程设计学报, 2022, 29(5): 547-554.
[4] 钟道方, 田颖, 张明路. 轮腿式爬壁机器人的永磁吸附装置设计与优化[J]. 工程设计学报, 2022, 29(1): 41-50.
[5] 刘永江, 彭宣霖, 唐雄辉, 李华, 齐紫梅. 轴流散热风机共振失效分析与优化设计[J]. 工程设计学报, 2021, 28(2): 203-209.
[6] 唐东林, 龙再勇, 汤炎锦, 潘峰, 游传坤. 储罐检测爬壁机器人全遍历路径规划[J]. 工程设计学报, 2020, 27(2): 162-171.
[7] 汤亮, 何仁杰, 龚发云, 李飞扬, 刘冠军, 杨敏. 变风载下风电齿轮箱内部激励规律研究及动态特性优化[J]. 工程设计学报, 2020, 27(2): 212-222.
[8] 刘春青, 王文汉. 基于人工神经网络-遗传算法的展成法球面精密磨削参数优化[J]. 工程设计学报, 2019, 26(4): 395-402.
[9] 王艾伦, 刘乐, 刘庆亚. 基于Kriging代理模型的拉杆组合转子强度可靠性研究[J]. 工程设计学报, 2019, 26(4): 433-440.
[10] 唐东林, 李茂扬, 丁超, 魏子兵, 胡琳, 袁波. 轮式爬壁机器人转向稳定性研究[J]. 工程设计学报, 2019, 26(2): 153-161.
[11] 魏春雨, 蔡月, 刘明贺, 张琦, 贾乾忠. 新型车载医疗救护隔振平台设计及仿真[J]. 工程设计学报, 2018, 25(5): 532-538.
[12] 唐东林, 袁波, 胡琳, 李茂扬, 魏子兵. 储罐探伤爬壁机器人全遍历路径规划方法[J]. 工程设计学报, 2018, 25(3): 253-261.
[13] 李彦奎, 吕彦明, 倪明明. 基于正交试验的航空叶片精锻模具磨损分析[J]. 工程设计学报, 2017, 24(6): 632-637.
[14] 王波, GEA Haechang, 白俊强, 张玉东, 宫建, 张卫民. 基于Stochastic Kriging模型的不确定性序贯试验设计方法[J]. 工程设计学报, 2016, 23(6): 530-536.
[15] 邱瑞斌, 雷飞, 陈园, 王琼. 基于权重比的车架多工况拓扑优化方法研究[J]. 工程设计学报, 2016, 23(5): 444-452.