• 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

鞋类位置检测系统中的激光传感器与摄像头视觉分析

Analysis of Laser Sensors and Camera Vision in the Shoe Position Inspection System.

作者信息

Klarák Jaromír, Kuric Ivan, Zajačko Ivan, Bulej Vladimír, Tlach Vladimír, Józwik Jerzy

机构信息

Faculty of Mechanical Engineering, University of Žilina, 010 26 Žilina, Slovakia.

Institute of Informatics, Slovak Academy of Sciences, 845 07 Bratislava, Slovakia.

出版信息

Sensors (Basel). 2021 Nov 12;21(22):7531. doi: 10.3390/s21227531.

DOI:10.3390/s21227531
PMID:34833604
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8620823/
Abstract

Inspection systems are currently an evolving field in the industry. The main goal is to provide a picture of the quality of intermediates and products in the production process. The most widespread sensory system is camera equipment. This article describes the implementation of camera devices for checking the location of the upper on the shoe last. The next part of the article deals with the analysis of the application of laser sensors in this task. The results point to the clear advantages of laser sensors in the inspection task of placing the uppers on the shoe's last. The proposed method defined the resolution of laser scanners according to the type of scanned surface, where the resolution of point cloud ranged from 0.16 to 0.5 mm per point based on equations representing specific points approximated to polynomial regression in specific places, which are defined in this article. Next, two inspection systems were described, where one included further development in the field of automation and Industry 4.0 and with a high perspective of development into the future. The main aim of this work is to conduct analyses of sensory systems for inspection systems and their possibilities for further work mainly based on the resolution and quality of obtained data. For instance, dependency on scanning complex surfaces and the achieved resolution of scanned surfaces.

摘要

检测系统目前是该行业中一个不断发展的领域。主要目标是提供生产过程中中间体和产品质量的情况。最广泛使用的传感系统是摄像设备。本文描述了用于检查鞋帮在鞋楦上位置的摄像设备的应用。本文的下一部分讨论了激光传感器在这项任务中的应用分析。结果表明激光传感器在将鞋帮放置在鞋楦上的检测任务中具有明显优势。所提出的方法根据扫描表面的类型定义了激光扫描仪的分辨率,基于本文中定义的特定点近似为多项式回归的方程,点云的分辨率为每点0.16至0.5毫米。接下来描述了两个检测系统,其中一个包括自动化和工业4.0领域的进一步发展以及具有很高的未来发展前景。这项工作的主要目的是对检测系统的传感系统及其进一步工作的可能性进行分析,主要基于所获得数据的分辨率和质量。例如,对扫描复杂表面的依赖性以及扫描表面所达到的分辨率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/07161e1eea43/sensors-21-07531-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/7982f63cc94b/sensors-21-07531-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/4770b130518a/sensors-21-07531-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/447e5f998fa8/sensors-21-07531-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/29ba7ba85d08/sensors-21-07531-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/5f7a213a1ea5/sensors-21-07531-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/8d540c402399/sensors-21-07531-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/cb9c903ae74e/sensors-21-07531-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/3ee70f6c1a79/sensors-21-07531-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/2bfc9b0387ef/sensors-21-07531-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/423723ad42f0/sensors-21-07531-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/d9d26e39f6c5/sensors-21-07531-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/fff9c14ef1ae/sensors-21-07531-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/fcd95f2aee98/sensors-21-07531-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/85ca1635eecc/sensors-21-07531-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/dda4796a9e49/sensors-21-07531-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/668362f65107/sensors-21-07531-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/f93a9c102a94/sensors-21-07531-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/1a37d2bb15b4/sensors-21-07531-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/07161e1eea43/sensors-21-07531-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/7982f63cc94b/sensors-21-07531-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/4770b130518a/sensors-21-07531-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/447e5f998fa8/sensors-21-07531-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/29ba7ba85d08/sensors-21-07531-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/5f7a213a1ea5/sensors-21-07531-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/8d540c402399/sensors-21-07531-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/cb9c903ae74e/sensors-21-07531-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/3ee70f6c1a79/sensors-21-07531-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/2bfc9b0387ef/sensors-21-07531-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/423723ad42f0/sensors-21-07531-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/d9d26e39f6c5/sensors-21-07531-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/fff9c14ef1ae/sensors-21-07531-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/fcd95f2aee98/sensors-21-07531-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/85ca1635eecc/sensors-21-07531-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/dda4796a9e49/sensors-21-07531-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/668362f65107/sensors-21-07531-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/f93a9c102a94/sensors-21-07531-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/1a37d2bb15b4/sensors-21-07531-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370f/8620823/07161e1eea43/sensors-21-07531-g019.jpg

相似文献

1
Analysis of Laser Sensors and Camera Vision in the Shoe Position Inspection System.鞋类位置检测系统中的激光传感器与摄像头视觉分析
Sensors (Basel). 2021 Nov 12;21(22):7531. doi: 10.3390/s21227531.
2
Design of the Automated Calibration Process for an Experimental Laser Inspection Stand.实验性激光检测台自动校准过程的设计。
Sensors (Basel). 2022 Jul 15;22(14):5306. doi: 10.3390/s22145306.
3
Exposure to dust and its particle size distribution in shoe manufacture and repair workplaces measured with GRIMM laser dust monitor.使用格林激光粉尘监测仪测量鞋类制造和维修工作场所的粉尘暴露及其粒径分布。
Int J Occup Med Environ Health. 2003;16(4):321-8.
4
Curvature generation based on weight-updated boosting using shoe last point-cloud measurements.基于鞋楦点云测量的权重更新增强算法生成曲率。
Heliyon. 2024 Feb 20;10(4):e26498. doi: 10.1016/j.heliyon.2024.e26498. eCollection 2024 Feb 29.
5
Fast and accurate centerline extraction algorithm for a laser stripe applied for shoe outsole inspection.用于鞋外底检测的激光条纹快速准确中心线提取算法
Appl Opt. 2023 Jan 10;62(2):314-324. doi: 10.1364/AO.476939.
6
Analysis of the Possibilities of Tire-Defect Inspection Based on Unsupervised Learning and Deep Learning.基于无监督学习和深度学习的轮胎缺陷检测可能性分析。
Sensors (Basel). 2021 Oct 25;21(21):7073. doi: 10.3390/s21217073.
7
Development of a Remote Displacement Measuring Laser System for Bridge Inspection.桥梁检测用远程位移测量激光系统的研制。
Sensors (Basel). 2022 Mar 2;22(5):1963. doi: 10.3390/s22051963.
8
Football playing surface and shoe design affect rotational traction.足球比赛场地和鞋类设计会影响旋转牵引力。
Am J Sports Med. 2009 Mar;37(3):518-25. doi: 10.1177/0363546508328108. Epub 2009 Jan 23.
9
An Improved Low-Noise Processing Methodology Combined with PCL for Industry Inspection Based on Laser Line Scanner.一种基于激光线扫描仪的、结合点云库(PCL)用于工业检测的改进型低噪声处理方法。
Sensors (Basel). 2019 Aug 2;19(15):3398. doi: 10.3390/s19153398.
10
Technical evaluation of a CAD system for orthopaedic shoe-upper design.用于矫形鞋帮设计的计算机辅助设计系统的技术评估
Proc Inst Mech Eng H. 1991;205(2):109-15. doi: 10.1243/PIME_PROC_1991_205_276_02.

引用本文的文献

1
Current State of the Art and Potential for Construction and Demolition Waste Processing: A Scoping Review of Sensor-Based Quality Monitoring and Control for In- and Online Implementation in Production Processes.建筑与拆除废物处理的当前技术水平及潜力:基于传感器的质量监测与控制在生产过程中现场及在线实施的范围综述
Sensors (Basel). 2025 Jul 14;25(14):4401. doi: 10.3390/s25144401.
2
Autoencoders Based on 2D Convolution Implemented for Reconstruction Point Clouds from Line Laser Sensors.基于二维卷积的自动编码器实现从线激光传感器重建点云。
Sensors (Basel). 2023 May 15;23(10):4772. doi: 10.3390/s23104772.
3
Design of the Automated Calibration Process for an Experimental Laser Inspection Stand.

本文引用的文献

1
Data Analytics in Industry 4.0: A Survey.工业4.0中的数据分析:一项调查。
Inf Syst Front. 2021 Aug 24:1-17. doi: 10.1007/s10796-021-10190-0.
2
Advances in Sensor Technologies in the Era of Smart Factory and Industry 4.0.智能工厂和工业 4.0 时代的传感器技术进展。
Sensors (Basel). 2020 Nov 27;20(23):6783. doi: 10.3390/s20236783.
3
A Customer Feedback Platform for Vehicle Manufacturing Compliant with Industry 4.0 Vision.面向工业 4.0 愿景的车辆制造合规性客户反馈平台。
实验性激光检测台自动校准过程的设计。
Sensors (Basel). 2022 Jul 15;22(14):5306. doi: 10.3390/s22145306.
Sensors (Basel). 2018 Oct 1;18(10):3298. doi: 10.3390/s18103298.
4
Robust laser stripe extraction for three-dimensional reconstruction based on a cross-structured light sensor.基于交叉结构光传感器的用于三维重建的稳健激光条纹提取
Appl Opt. 2017 Feb 1;56(4):823-832. doi: 10.1364/AO.56.000823.
5
A computational approach to edge detection.一种基于计算的边缘检测方法。
IEEE Trans Pattern Anal Mach Intell. 1986 Jun;8(6):679-98.