Separation method of bending and torsion in shape sensing based on FBG sensors array

扭转(腹足类) 曲率 弯曲分子几何 光学 材料科学 弯曲半径 曲率半径 波长 弯曲 物理 声学 几何学 数学 平均曲率 复合材料 流量平均曲率 医学 外科
作者
Xinhua Yi,Xiangyan Chen,Hongchao Fan,Fei Shi,Xiaomin Cheng,Jinwu Qian
出处
期刊:Optics Express [Optica Publishing Group]
卷期号:28 (7): 9367-9367 被引量:52
标识
DOI:10.1364/oe.386738
摘要

This paper presents a theoretical method for separating bending and torsion of shape sensing sensor to improve sensing accuracy during its deformation. We design a kind of shape sensing sensor by encapsulating three fibers on the surface of a flexible rod and forming a triangular FBG sensors array. According to the configuration of FBG sensors array, we derive the relationship between bending curvature and bending strain, and set up a function about the packaging angle of FBG sensor and strain induced by torsion under different twist angles. Combined with the influence of bending and torsion on strain, we establish a nonlinear matrix equation resolving three unknown parameters including maximum strain, bending direction and wavelength shift induced by torsion and temperature. The three parameters are sufficient to separate bending and torsion, and acquire two scalar functions including curvature and torsion, which could describe 3D shape of rod according to Frenet-Serret formulas. Experimental results show that the relative average error of measurement about maximum strain, bending direction is respectively 2.65% and 0.86% when shape-sensing sensor is bent into an arc with a radius of 260 mm. The separating method also applied to 2D shape and 3D shape of reconstruction, and the absolute spatial position maximum error is respectively 3.79mm and 11.10mm when shape-sensing sensor with length 500mm is bent into arc shape with a radius 260mm and helical curve. The experiment results verify the feasibility of separating method, which would provide effective parameters for precise 3D reconstruction model of shape sensing sensor.
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
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
Anthony完成签到,获得积分10
刚刚
刚刚
淡淡雪碧完成签到,获得积分10
1秒前
老年人完成签到,获得积分10
2秒前
Criminology34应助焦糖小猫咪采纳,获得10
3秒前
Hello应助DearWhite采纳,获得10
3秒前
GingerF应助小糖使采纳,获得50
4秒前
开朗发卡完成签到,获得积分10
4秒前
SciGPT应助年入百万采纳,获得10
5秒前
ewmmel完成签到 ,获得积分10
5秒前
汪欣怡完成签到,获得积分10
6秒前
六子完成签到,获得积分10
6秒前
Weizhuo完成签到 ,获得积分10
7秒前
脑洞疼应助YIZEXIN采纳,获得10
7秒前
jun完成签到,获得积分10
7秒前
华仔应助大气雨旋采纳,获得10
8秒前
Jasper应助搞怪的又蓝采纳,获得10
8秒前
何静完成签到 ,获得积分10
11秒前
11秒前
张赫兹完成签到,获得积分10
11秒前
Livtales完成签到 ,获得积分10
11秒前
木子完成签到,获得积分10
12秒前
wwww应助科研通管家采纳,获得10
13秒前
桐桐应助科研通管家采纳,获得10
13秒前
yls123发布了新的文献求助10
13秒前
huau应助科研通管家采纳,获得30
13秒前
ding应助科研通管家采纳,获得10
13秒前
大个应助科研通管家采纳,获得10
13秒前
13秒前
14秒前
今后应助科研通管家采纳,获得10
14秒前
学pde的小丸子完成签到,获得积分10
14秒前
初景应助科研通管家采纳,获得20
14秒前
科研通AI2S应助科研通管家采纳,获得10
14秒前
CipherSage应助科研通管家采纳,获得10
14秒前
情怀应助科研通管家采纳,获得10
14秒前
15秒前
斯文败类应助科研通管家采纳,获得10
15秒前
15秒前
15秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Effects of Two Weeks of Red Light Therapy on Choroidal Thickness and Axial Length in Young Adults 700
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The Neuroscience of Language 400
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 400
Too Much of Two Good Things: Investment Protection and Environmental Protection in International Law 260
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7673641
求助须知:如何正确求助?哪些是违规求助? 9240184
关于积分的说明 19904669
捐赠科研通 7243327
什么是DOI,文献DOI怎么找? 3285626
关于科研通互助平台的介绍 2443768
邀请新用户注册赠送积分活动 2287930