首页> 外文OA文献 >An Automated Sensing System for Steel Bridge Inspection Using GMR Sensor Array and Magnetic Wheels of Climbing Robot
【2h】

An Automated Sensing System for Steel Bridge Inspection Using GMR Sensor Array and Magnetic Wheels of Climbing Robot

机译:基于GMR传感器阵列和攀岩机器人磁轮的钢桥自动检测传感系统

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Corrosion is one of the main causes of deterioration of steel bridges. It may cause metal loss and fatigue cracks in the steel components, which would lead to the collapse of steel bridges. This paper presents an automated sensing system to detect corrosion, crack, and other kinds of defects using a GMR (Giant Magnetoresistance) sensor array. Defects will change the relative permeability and electrical conductivity of the material. As a result, magnetic field density generated by ferromagnetic material and the magnetic wheels will be changed. The defects are able to be detected by using GMR sensor array to measure the changes of magnetic flux density. In this study, magnetic wheels are used not only as the adhesion device of the robot, but also as an excitation source to provide the exciting magnetic field for the sensing system. Furthermore, compared to the eddy current method and the MFL (magnetic flux leakage) method, this sensing system suppresses the noise from lift-off value fluctuation by measuring the vertical component of induced magnetic field that is perpendicular to the surface of the specimen in the corrosion inspection. Simulations and experimental results validated the feasibility of the system for the automated defect inspection.
机译:腐蚀是钢桥劣化的主要原因之一。这可能会导致金属损失和钢部件中的疲劳裂纹,从而导致钢桥倒塌。本文介绍了一种自动感应系统,可使用GMR(巨磁阻)传感器阵列检测腐蚀,裂缝和其他类型的缺陷。缺陷会改变材料的相对磁导率和电导率。结果,由铁磁材料和磁性轮产生的磁场密度将改变。可以通过使用GMR传感器阵列测量磁通密度的变化来检测缺陷。在这项研究中,磁轮不仅用作机器人的附着装置,而且还用作激励源,为传感系统提供激励磁场。此外,与涡流法和MFL(漏磁通)法相比,该传感系统通过测量垂直于试样表面的感应磁场的垂直分量来抑制来自提离值波动的噪声。腐蚀检查。仿真和实验结果验证了该系统用于自动缺陷检查的可行性。

著录项

  • 作者

    Wang Rui; Kawamura Youhei;

  • 作者单位
  • 年度 2016
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号