Experimental and Numerical Optimization of Magnetic Adhesion Force for Wall Climbing Robot Applications

粘附 机器人 攀登 计算机科学 材料科学 结构工程 工程类 复合材料 人工智能
作者
Anwar Sahbel,Ayman Abbas,TP Sattar
出处
期刊:International journal of mechanical engineering and robotics research [EJournal Publishing]
卷期号:: 18-24 被引量:4
标识
DOI:10.18178/ijmerr.8.1.18-24
摘要

Wall climbing robots require adhesion methods which are suited to the climbing surface material and roughness. In this paper, an optimum design of a magnetic adhesion mechanism has been developed for ferrous surfaces that maximises the magnetic adhesion force. This in turn maximises the payload that can be carried by the climbing robot. Experiments have been designed using the Response Surface Methodology (RSM) to study the effect of identified independent parameters (namely the distance between magnets, air gap and yoke thickness) that affect the response variable i.e. the magnetic adhesion force. A quadratic regression model has been developed to represent an empirical relationship between the response variable and the independent variables. Statistical analysis of the predicted model has been investigated using analysis of variance (ANOVA). To inspect the adequacy of the predicted quadratic model, validating experiments have been carried out at different conditions where the experimental results showed similar response values to the predicted model responses. Numerical optimisation has been applied to predict the optimum variable conditions for maximum adhesion force and air gap, resulting in an adhesion force of 240.3 N at 20 mm distance between magnets, 18.5 mm air gap and 8.3 mm yoke thickness. The optimum conditions have been numerically validated using a commercial finite element simulator. The numerically optimised design parameters have been used to design and construct a prototype wall climbing robot.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
1秒前
不予发布了新的文献求助10
2秒前
2秒前
悦耳的机器猫完成签到,获得积分10
3秒前
3秒前
科研通AI2S应助jason04124采纳,获得10
3秒前
CDK发布了新的文献求助10
5秒前
Ashley完成签到,获得积分10
5秒前
Liu关闭了Liu文献求助
6秒前
陙兂完成签到,获得积分10
6秒前
小虫发布了新的文献求助10
6秒前
zj发布了新的文献求助10
6秒前
6秒前
6秒前
jjjjjj完成签到,获得积分10
6秒前
可爱的函函应助YA采纳,获得10
6秒前
香蕉觅云应助王露阳采纳,获得10
6秒前
7秒前
共享精神应助科研通管家采纳,获得10
9秒前
9秒前
ming应助科研通管家采纳,获得10
9秒前
英姑应助科研通管家采纳,获得10
9秒前
彭于晏应助科研通管家采纳,获得10
9秒前
9秒前
9秒前
Dai完成签到 ,获得积分10
10秒前
爆米花应助斯文天曼采纳,获得10
10秒前
Gleast发布了新的文献求助10
11秒前
baby709466应助Y哦莫哦莫采纳,获得10
12秒前
12秒前
14秒前
15秒前
小虫完成签到,获得积分10
15秒前
15秒前
16秒前
16秒前
17秒前
xlj完成签到,获得积分10
18秒前
高分求助中
Licensing Deals in Pharmaceuticals 2019-2024 3000
Effect of reactor temperature on FCC yield 2000
Very-high-order BVD Schemes Using β-variable THINC Method 1020
Impiego dell’associazione acetazolamide/pentossifillina nel trattamento dell’ipoacusia improvvisa idiopatica in pazienti affetti da glaucoma cronico 900
錢鍾書楊絳親友書札 800
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 800
Mission to Mao: Us Intelligence and the Chinese Communists in World War II 600
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3297232
求助须知:如何正确求助?哪些是违规求助? 2932727
关于积分的说明 8458768
捐赠科研通 2605447
什么是DOI,文献DOI怎么找? 1422342
科研通“疑难数据库(出版商)”最低求助积分说明 661364
邀请新用户注册赠送积分活动 644655