Surface and back-side defects identification combined with magnetic flux leakage and boundary magnetic perturbation

Author:

Ou Zhengyu1ORCID,Han Zandong12ORCID,Yang Chenghao1,Dong Shihao1,Du Dong13

Affiliation:

1. Department of Mechanical Engineering, Tsinghua University, Beijing 10084, China

2. State Key Laboratory of Tribology, Tsinghua University, Beijing 10084, China

3. Key Laboratory for Advanced Materials Processing Technology, Ministry of Education, Beijing 10084, China

Abstract

In magnetic flux leakage (MFL) detection, the identification of surface and back-side defects is required to obtain more accurate defect quantification and risk assessment results. However, current MFL techniques can detect both surface and back-side defects but are generally unable to distinguish between them. Therefore, this paper proposes a new boundary magnetic perturbation (BMP) testing method, combining the results of MFL to distinguish between surface and back-side defects. First, the detection mechanism of the BMP testing method and the impact of the tested magnetic flux density components are presented and analyzed by simulations to further develop an identification method. Then, the influences of the BMP sensor’s lift-off and installation position are investigated by experiments to improve distinguishing performance. Finally, the repeated measurements show that the surface and back-side defects within the wide range of sizes can be identified accurately, even when the defect depths are in the range of 12.5%–87.5% of the sample thickness. Furthermore, the BMP testing method neither increases the length of the detection device nor requires additional magnetizers or signal generators. Therefore, the proposed method is highly suitable for the existing MFL detection devices to distinguish between surface and back-side defects.

Publisher

AIP Publishing

Subject

Instrumentation

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3