• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

基于背散射X射线的夹层结构面板侧焊接位置检测方法研究

Research on the Weld Position Detection Method for Sandwich Structures from Face-Panel Side Based on Backscattered X-ray.

作者信息

Wei Angang, Chang Baohua, Xue Boce, Peng Guodong, Du Dong, Han Zandong

机构信息

Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.

Key Laboratory for Advanced Materials Processing Technology, Ministry of Education, Beijing 100084, China.

出版信息

Sensors (Basel). 2019 Jul 20;19(14):3198. doi: 10.3390/s19143198.

DOI:10.3390/s19143198
PMID:31330774
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6679273/
Abstract

Web-core sandwich panels are a typical lightweight structure utilized in a variety of fields, such as naval, aviation, aerospace, etc. Welding is considered as an effective process to join the face panel to the core panel from the face panel side. However, it is difficult to locate the joint position (i.e., the position of core panel) due to the shielding of the face panel. This paper studies a weld position detection method based on X-ray from the face panel side for aluminum web-core sandwich panels used in aviation and naval structures. First, an experimental system was designed for weld position detection, able to quickly acquire the X-ray intensity signal backscattered by the specimen. An effective signal processing method was developed to accurately extract the characteristic value of X-ray intensity signals representing the center of the joint. Secondly, an analytical model was established to calculate and optimize the detection parameters required for detection of the weld position of a given specimen by analyzing the relationship between the backscattered X-ray intensity signal detected by the detector and the parameters of the detection system and specimen during the detection process. Finally, several experiments were carried out on a 6061 aluminum alloy specimen with a thickness of 3 mm. The experimental results demonstrate that the maximum absolute error of the detection was 0.340 mm, which is sufficiently accurate for locating the position of the joint. This paper aims to provide the technical basis for the automatic tracking of weld joints from the face panel side, required for the high-reliability manufacturing of curved sandwich structures.

摘要

腹板-芯材夹芯板是一种典型的轻质结构,应用于海军、航空、航天等多个领域。焊接被认为是从面板侧将面板与芯板连接的有效工艺。然而,由于面板的遮挡,难以确定接头位置(即芯板的位置)。本文研究了一种基于X射线从面板侧检测航空和海军结构中使用的铝制腹板-芯材夹芯板焊接位置的方法。首先,设计了一个用于焊接位置检测的实验系统,能够快速采集被试件反向散射的X射线强度信号。开发了一种有效的信号处理方法,以准确提取代表接头中心的X射线强度信号的特征值。其次,通过分析检测过程中探测器检测到的反向散射X射线强度信号与检测系统和试件参数之间的关系,建立了一个分析模型,用于计算和优化检测给定试件焊接位置所需的检测参数。最后,对厚度为3mm的6061铝合金试件进行了多次实验。实验结果表明,检测的最大绝对误差为0.340mm,对于确定接头位置来说足够精确。本文旨在为曲面夹芯结构高可靠性制造所需的从面板侧自动跟踪焊接接头提供技术依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/38a073a314e4/sensors-19-03198-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/c861a9e40186/sensors-19-03198-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/7491c8809df3/sensors-19-03198-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/7a302f6c9dfd/sensors-19-03198-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/784f7e98bdb9/sensors-19-03198-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/45962a03c60f/sensors-19-03198-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/4b3c6b791c2f/sensors-19-03198-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/89c9228c66a9/sensors-19-03198-g007a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/1934a02853de/sensors-19-03198-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/f6a89c12a079/sensors-19-03198-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/b1b4f98e3b4e/sensors-19-03198-g010a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/750d4a1c55ea/sensors-19-03198-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/32f7035f8d2e/sensors-19-03198-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/d07d3cf0739b/sensors-19-03198-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/995b768e1180/sensors-19-03198-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/6b5adbb86520/sensors-19-03198-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/347d317b8ac1/sensors-19-03198-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/e13acb9498f7/sensors-19-03198-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/920e0b01b977/sensors-19-03198-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/38a073a314e4/sensors-19-03198-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/c861a9e40186/sensors-19-03198-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/7491c8809df3/sensors-19-03198-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/7a302f6c9dfd/sensors-19-03198-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/784f7e98bdb9/sensors-19-03198-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/45962a03c60f/sensors-19-03198-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/4b3c6b791c2f/sensors-19-03198-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/89c9228c66a9/sensors-19-03198-g007a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/1934a02853de/sensors-19-03198-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/f6a89c12a079/sensors-19-03198-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/b1b4f98e3b4e/sensors-19-03198-g010a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/750d4a1c55ea/sensors-19-03198-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/32f7035f8d2e/sensors-19-03198-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/d07d3cf0739b/sensors-19-03198-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/995b768e1180/sensors-19-03198-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/6b5adbb86520/sensors-19-03198-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/347d317b8ac1/sensors-19-03198-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/e13acb9498f7/sensors-19-03198-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/920e0b01b977/sensors-19-03198-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9564/6679273/38a073a314e4/sensors-19-03198-g019.jpg

相似文献

1
Research on the Weld Position Detection Method for Sandwich Structures from Face-Panel Side Based on Backscattered X-ray.基于背散射X射线的夹层结构面板侧焊接位置检测方法研究
Sensors (Basel). 2019 Jul 20;19(14):3198. doi: 10.3390/s19143198.
2
Research on the Weld Position Detection for the T-Joints in Web-Core Sandwich Panels Based on Eddy Current Technology.基于涡流技术的腹板芯材夹芯板T型接头焊接位置检测研究
Sensors (Basel). 2020 May 8;20(9):2691. doi: 10.3390/s20092691.
3
A Weld Position Recognition Method Based on Directional and Structured Light Information Fusion in Multi-Layer/Multi-Pass Welding.一种基于多层/多道焊接中方向光与结构光信息融合的焊缝位置识别方法
Sensors (Basel). 2018 Jan 5;18(1):129. doi: 10.3390/s18010129.
4
Magneto-optical imaging feature extraction of micro-gap weld joint under nonuniform magnetic field excitation.非均匀磁场激励下微间隙焊接接头的磁光成像特征提取
Appl Opt. 2019 Jan 10;58(2):291-301. doi: 10.1364/AO.58.000291.
5
Plastic Forming of Sandwich Panels and Numerical Analyses of the Forming Processes Based on Elastoplastic Equivalent Model.基于弹塑性等效模型的夹芯板塑性成型及成型过程数值分析
Materials (Basel). 2021 Aug 30;14(17):4955. doi: 10.3390/ma14174955.
6
In-Process Monitoring of Lack of Fusion in Ultra-Thin Sheets Edge Welding Using Machine Vision.使用机器视觉对超薄板边缘焊接中的未熔合进行过程监测。
Sensors (Basel). 2018 Jul 25;18(8):2411. doi: 10.3390/s18082411.
7
Grain fragmentation in ultrasonic-assisted TIG weld of pure aluminum.纯铝超声辅助TIG焊接中的晶粒破碎
Ultrason Sonochem. 2017 Nov;39:403-413. doi: 10.1016/j.ultsonch.2017.05.001. Epub 2017 May 3.
8
Dynamic response and optimal design of curved metallic sandwich panels under blast loading.爆炸载荷作用下曲面金属夹芯板的动态响应与优化设计
ScientificWorldJournal. 2014;2014:853681. doi: 10.1155/2014/853681. Epub 2014 Jul 10.
9
A Weld Joint Type Identification Method for Visual Sensor Based on Image Features and SVM.基于图像特征和 SVM 的视觉传感器焊接接头类型识别方法。
Sensors (Basel). 2020 Jan 14;20(2):471. doi: 10.3390/s20020471.
10
Dynamic Modeling of Weld Bead Geometry Features in Thick Plate GMAW Based on Machine Vision and Learning.基于机器视觉与学习的厚板气体保护金属极电弧焊焊缝几何特征动态建模
Sensors (Basel). 2020 Dec 11;20(24):7104. doi: 10.3390/s20247104.

引用本文的文献

1
Welding Seam Trajectory Recognition for Automated Skip Welding Guidance of a Spatially Intermittent Welding Seam Based on Laser Vision Sensor.基于激光视觉传感器的空间间歇焊缝自动跳焊引导的焊缝轨迹识别
Sensors (Basel). 2020 Jun 29;20(13):3657. doi: 10.3390/s20133657.
2
Research on the Weld Position Detection for the T-Joints in Web-Core Sandwich Panels Based on Eddy Current Technology.基于涡流技术的腹板芯材夹芯板T型接头焊接位置检测研究
Sensors (Basel). 2020 May 8;20(9):2691. doi: 10.3390/s20092691.

本文引用的文献

1
Ultrasonic Detection Method for Grouted Defects in Grouted Splice Sleeve Connector Based on Wavelet Pack Energy.基于子波包能量的预埋套筒灌浆连接接头缺陷超声检测方法
Sensors (Basel). 2019 Apr 6;19(7):1642. doi: 10.3390/s19071642.
2
Connection Mechanism of Molten Pool during Laser Transmission Welding of T-Joint with Minor Gap Presence.存在微小间隙的T型接头激光穿透焊接过程中熔池的连接机制
Materials (Basel). 2018 Sep 25;11(10):1823. doi: 10.3390/ma11101823.
3
Identification of Coffee Varieties Using Laser-Induced Breakdown Spectroscopy and Chemometrics.
利用激光诱导击穿光谱和化学计量学鉴定咖啡品种
Sensors (Basel). 2017 Dec 31;18(1):95. doi: 10.3390/s18010095.