利用主动热成像数据处理算法进行三维印刷表面缺陷检测

IF 2.3 4区 工程技术 Q3 ENGINEERING, MANUFACTURING 3D Printing and Additive Manufacturing Pub Date : 2023-06-01 Epub Date: 2023-06-08 DOI:10.1089/3dp.2021.0172
Ézio Carvalho de Santana, Wellington Francisco da Silva, Marcella Grosso Lima, Gabriela Ribeiro Pereira, Douglas Bressan Riffel
{"title":"利用主动热成像数据处理算法进行三维印刷表面缺陷检测","authors":"Ézio Carvalho de Santana, Wellington Francisco da Silva, Marcella Grosso Lima, Gabriela Ribeiro Pereira, Douglas Bressan Riffel","doi":"10.1089/3dp.2021.0172","DOIUrl":null,"url":null,"abstract":"<p><p>This article evaluates an active thermography algorithm to detect subsurface defects in materials made by additive manufacturing (AM). It is based on the techniques of thermographic signal reconstruction (TSR), thermal contrast, and the physical principles of heat transfer. The subsurface defects have different infill, depth, and size. The results obtained from this algorithm are compared with state-of-the-art TSR technique and show the high performance of the proposed algorithm even for subsurface defects done by 3D AM. The resulting images are better shown using the absolute difference in the place of variance. The proposed algorithm has higher contrast, better sensitivity to the defect depths, and lower noise than the TSR. The resultant image is quite clean and gives no doubt where the subsurface defects are.</p>","PeriodicalId":54341,"journal":{"name":"3D Printing and Additive Manufacturing","volume":"10 3","pages":"420-427"},"PeriodicalIF":2.3000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280207/pdf/","citationCount":"0","resultStr":"{\"title\":\"Three-Dimensional Printed Subsurface Defect Detection by Active Thermography Data-Processing Algorithm.\",\"authors\":\"Ézio Carvalho de Santana, Wellington Francisco da Silva, Marcella Grosso Lima, Gabriela Ribeiro Pereira, Douglas Bressan Riffel\",\"doi\":\"10.1089/3dp.2021.0172\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This article evaluates an active thermography algorithm to detect subsurface defects in materials made by additive manufacturing (AM). It is based on the techniques of thermographic signal reconstruction (TSR), thermal contrast, and the physical principles of heat transfer. The subsurface defects have different infill, depth, and size. The results obtained from this algorithm are compared with state-of-the-art TSR technique and show the high performance of the proposed algorithm even for subsurface defects done by 3D AM. The resulting images are better shown using the absolute difference in the place of variance. The proposed algorithm has higher contrast, better sensitivity to the defect depths, and lower noise than the TSR. The resultant image is quite clean and gives no doubt where the subsurface defects are.</p>\",\"PeriodicalId\":54341,\"journal\":{\"name\":\"3D Printing and Additive Manufacturing\",\"volume\":\"10 3\",\"pages\":\"420-427\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280207/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"3D Printing and Additive Manufacturing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1089/3dp.2021.0172\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/6/8 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"3D Printing and Additive Manufacturing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1089/3dp.2021.0172","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/6/8 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0

摘要

本文评估了一种检测增材制造(AM)材料次表面缺陷的主动热成像算法。该算法基于热成像信号重建 (TSR)、热对比和热传导物理原理等技术。次表面缺陷具有不同的填充度、深度和尺寸。将该算法获得的结果与最先进的 TSR 技术进行了比较,结果表明,即使是通过三维 AM 技术处理次表面缺陷,所提出的算法也具有很高的性能。用绝对差值代替方差,可以更好地显示生成的图像。与 TSR 相比,提议的算法对比度更高,对缺陷深度的灵敏度更高,噪声更低。生成的图像非常干净,不会让人怀疑次表面缺陷的位置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Three-Dimensional Printed Subsurface Defect Detection by Active Thermography Data-Processing Algorithm.

This article evaluates an active thermography algorithm to detect subsurface defects in materials made by additive manufacturing (AM). It is based on the techniques of thermographic signal reconstruction (TSR), thermal contrast, and the physical principles of heat transfer. The subsurface defects have different infill, depth, and size. The results obtained from this algorithm are compared with state-of-the-art TSR technique and show the high performance of the proposed algorithm even for subsurface defects done by 3D AM. The resulting images are better shown using the absolute difference in the place of variance. The proposed algorithm has higher contrast, better sensitivity to the defect depths, and lower noise than the TSR. The resultant image is quite clean and gives no doubt where the subsurface defects are.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
3D Printing and Additive Manufacturing
3D Printing and Additive Manufacturing Materials Science-Materials Science (miscellaneous)
CiteScore
6.00
自引率
6.50%
发文量
126
期刊介绍: 3D Printing and Additive Manufacturing is a peer-reviewed journal that provides a forum for world-class research in additive manufacturing and related technologies. The Journal explores emerging challenges and opportunities ranging from new developments of processes and materials, to new simulation and design tools, and informative applications and case studies. Novel applications in new areas, such as medicine, education, bio-printing, food printing, art and architecture, are also encouraged. The Journal addresses the important questions surrounding this powerful and growing field, including issues in policy and law, intellectual property, data standards, safety and liability, environmental impact, social, economic, and humanitarian implications, and emerging business models at the industrial and consumer scales.
期刊最新文献
Experimental Study on Interfacial Shear Behavior of 3D Printed Recycled Mortar. Characterizing the Effect of Filament Moisture on Tensile Properties and Morphology of Fused Deposition Modeled Polylactic Acid/Polybutylene Succinate Parts. On the Development of Smart Framework for Printability Maps in Additive Manufacturing of AISI 316L Stainless Steel. Rapid Fabrication of Silica Microlens Arrays via Glass 3D Printing. Simulation of Binder Jetting and Analysis of Magnesium Alloy Bonding Mechanism.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1