1.福建永越智能科技股份有限公司,福州 350001
2.福州大学 机械工程及自动化学院,福州 350116
SHEN Shunxi, E-mail: 15985705866@163.com
收稿:2025-03-07,
修回:2025-05-03,
纸质出版:2025-11-15
移动端阅览
沈顺喜,陈立志,涂德贵,等. 基于Halbach的爬壁机器人永磁组件的设计与优化[J]. 机械强度,2025,47(11):135-141.
SHEN Shunxi,CHEN Lizhi,TU Degui,et al. Design and optimization of the permanent magnet assembly for wall-climbing robots based on Halbach[J]. Journal of Mechanical Strength,2025,47(11):135-141.
沈顺喜,陈立志,涂德贵,等. 基于Halbach的爬壁机器人永磁组件的设计与优化[J]. 机械强度,2025,47(11):135-141. DOI: 10.16579/j.issn.1001.9669.2025.11.016.
SHEN Shunxi,CHEN Lizhi,TU Degui,et al. Design and optimization of the permanent magnet assembly for wall-climbing robots based on Halbach[J]. Journal of Mechanical Strength,2025,47(11):135-141. DOI: 10.16579/j.issn.1001.9669.2025.11.016.
针对传统爬壁机器人永磁组件吸附力与重量失衡、漏磁严重及吸附效率低的问题,为提升其在钢制壁面的磁吸附性能,满足船舶、塔筒等复杂环境作业需求,开展了Halbach永磁组件的设计与优化研究。选用N40M钕铁硼与Q235钢分别作为永磁体与轭铁材料,设计了类梯形Halbach永磁组件,上侧增设轭铁以引导磁感线减小漏磁,侧边不设轭铁;基于麦克斯韦方程组与应力张力法,建立了吸附力有限元仿真模型,采用控制变量法系统分析组件长度、宽度、厚度及轭铁厚度的影响;在尺寸约束下,通过非线性规划(Method of Moving Asymptotes
MMA)算法优化参数,搭建了岛津AGX-V2型拉伸机试验台,验证了仿真结果的正确性。结果表明,优化后吸附力从3 500.6 N提升至3 755.3 N,增幅7.28%;试验与仿真曲线趋势一致,最大吸附力偏差为8.1%,验证了仿真模型的准确性,为爬壁机器人吸附系统优化提供依据。
Aimed at the problems of unbalanced adsorption force and weight
severe magnetic flux leakage
and low adsorption efficiency of permanent magnet assemblies in traditional wall-climbing robots
to improve their magnetic adsorption performance on steel walls and meet the operation requirements in complex environments such as ships and tower drums
a study on the design and optimization of Halbach permanent magnet assemblies was carried out. N40M neodymium-iron-boron and Q235 steel were selected as the permanent magnet and yoke materials respectively
and a trapezoid-like Halbach permanent magnet assembly was designed. A yoke was added on the upper side to guide magnetic induction lines and reduce magnetic flux leakage
while no yoke was arranged on the side. Based on Maxwell's equations and the stress tensor method
a finite element simulation model of adsorption force was established. The control variable method was adopted to systematically analyze the influences of assembly length
width
thickness
and yoke thickness. Under size constraints
parameters were optimized via the nonlinear programming method of moving asymptotes (MMA) algorithm. Finally
a Shimadzu AGX-V2 tensile testing machine platform was built
loaded at a speed of 0.2 mm/s with equipment gravity deducted
to verify the simulation results.After optimization
the adsorption force was increased from 3 500.6 N to 3 755.3 N
with an increase of 7.28%. The test and simulation curves showed a consistent trend
and the maximum adsorption force deviation was 8.1%
which verified the accuracy of the simulation model and provided a basis for the optimization of the adsorption system of wall-climbing robots.
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