[1]胡绍杰,彭如恕,何 凯,等.履带式爬壁机器人磁吸附单元优化设计与实验研究[J].机械与电子,2018,(01):69-74.
 HU Shaojie,PENG Rushu,HE Kai,et al.Optimal Design and Experimental Study on Magnetic Adsorption Unit of Crawler-Type Wall-Climbing Robot[J].Machinery & Electronics,2018,(01):69-74.
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履带式爬壁机器人磁吸附单元优化设计与实验研究
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2018年01期
页码:
69-74
栏目:
智能工程
出版日期:
2018-01-24

文章信息/Info

Title:
Optimal Design and Experimental Study on Magnetic Adsorption Unit of Crawler-Type Wall-Climbing Robot
文章编号:
1001-2257(2018)01-0069-06
作者:
胡绍杰12彭如恕1何 凯2李纠华2蔡建楠23周 维23
(1. 南华大学机械工程学院,湖南 衡阳 421001; 2. 中国科学院深圳先进技术研究院精密工程中心,广东 深圳 518055; 3. 中国石油大学化学工程学院,北京 102249)
Author(s):
HU Shaojie12 PENG Rushu1 HE Kai2LI Jiuhua2 CAI Jiannan23 ZHOU Wei23
(1.School of Mechanical Engineering, University of South China, Hengyang 421001, China; 2.Precision Engineering Center, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen 518055,China; 3.College of Chemical Engineering, China
关键词:
爬壁机器人 吸附单元 优化设计 轻量化设计
Keywords:
wall-climbing robot adsorption unit optimization design lightweight design
分类号:
TH161
文献标志码:
A
摘要:
为了使爬壁机器人结构紧凑、轻量化程度高,提出了一种既可增加吸附能力,又不增加自身重量的新型吸附单元结构方案。首先,运用有限元方法,建立磁力三维理论计算模型,对关键参数进行定量分析,得到各个参数与吸附力的关系图。然后,采用多因素分析的方法,对主要关键参数进行了优化分析。通过实验验证,实验结果与仿真计算数据基本吻合。经过优化后,吸附力提升了21.4%,达到628 N,验证了优化方法的合理性,为爬壁机器人的轻量化设计提供了依据。
Abstract:
This paper presents a structure scheme of a new adsorption unit which can increase the adsorption capacity while not adding its weight. Firstly, the method of finite element was used to establish the three-dimensional theoretical calculation model of magnetic force, thus the key parameters were quantitatively analyzed, in this way, the relation schema of the parameters and the adsorption force was obtained. Then, the multi-factor analysis method was adopted to optimize the analysis of the main key parameters. It was found that the experimental results were basically consistent with the simulation data. After optimization, the adsorption force increased by 21.4% to 628 N, which verifies the rationality of the optimization method, providing a basis for the lightweight design of wall-climbing robots.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2017-10-16
作者简介:胡绍杰(1991-),男,河南信阳人,硕士研究生,研究方向为非标自动化设备与工业机器人; 彭如恕(1963-),男,湖南邵东人,教授,硕士研究生导师,研究方向为激光加工与应用研究。
更新日期/Last Update: 2018-01-24