Alexander Gall, Anja Heim, Patrick Weinberger, Bernhard Fröhler, Johann Kastner, Christoph Heinzl
{"title":"沉浸式检测:使用AR中的x射线计算机断层扫描数据进行直观的材料分析","authors":"Alexander Gall, Anja Heim, Patrick Weinberger, Bernhard Fröhler, Johann Kastner, Christoph Heinzl","doi":"10.1007/s10921-025-01220-x","DOIUrl":null,"url":null,"abstract":"<div><p>Material analyses based on X-ray computed tomography (XCT) imaging are typically conducted away from scanning facilities, in separate office environments on 2D displays. This separation hinders on-site analysis, and due to the lack of spatial representation, limits the effective exploration of the material structure. We present a novel augmented reality (AR) framework enabling in-situ visualization of non-destructive testing (NDT) data spatially registered with real specimens. Our approach facilitates comprehensive exploration of primary and secondary XCT data, enabling researchers to inspect material properties onsite and in-place. Coupling immersive visualization techniques with real physical objects allows for highly intuitive workflows in material analysis and inspection, which enables the identification of anomalies and accelerates informed decision making. The AR framework offers automatic material recognition, hands-free workflows and embodied interaction with physical samples, generating an engaging analytical experience. A case study on fiber-reinforced polymer datasets was used to validate the AR framework and its new workflow. Expert evaluations revealed significant improvements in spatial data comprehension and more natural interaction compared to conventional analysis systems. This study demonstrates the potential of immersive AR technologies to enhance industrial materials analysis, providing preliminary insights for integrating such immersive approaches.</p></div>","PeriodicalId":655,"journal":{"name":"Journal of Nondestructive Evaluation","volume":"44 3","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2025-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10921-025-01220-x.pdf","citationCount":"0","resultStr":"{\"title\":\"Immersive Inspection: Intuitive Material Analysis using X-Ray Computed Tomography Data in AR\",\"authors\":\"Alexander Gall, Anja Heim, Patrick Weinberger, Bernhard Fröhler, Johann Kastner, Christoph Heinzl\",\"doi\":\"10.1007/s10921-025-01220-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Material analyses based on X-ray computed tomography (XCT) imaging are typically conducted away from scanning facilities, in separate office environments on 2D displays. This separation hinders on-site analysis, and due to the lack of spatial representation, limits the effective exploration of the material structure. We present a novel augmented reality (AR) framework enabling in-situ visualization of non-destructive testing (NDT) data spatially registered with real specimens. Our approach facilitates comprehensive exploration of primary and secondary XCT data, enabling researchers to inspect material properties onsite and in-place. Coupling immersive visualization techniques with real physical objects allows for highly intuitive workflows in material analysis and inspection, which enables the identification of anomalies and accelerates informed decision making. The AR framework offers automatic material recognition, hands-free workflows and embodied interaction with physical samples, generating an engaging analytical experience. A case study on fiber-reinforced polymer datasets was used to validate the AR framework and its new workflow. Expert evaluations revealed significant improvements in spatial data comprehension and more natural interaction compared to conventional analysis systems. This study demonstrates the potential of immersive AR technologies to enhance industrial materials analysis, providing preliminary insights for integrating such immersive approaches.</p></div>\",\"PeriodicalId\":655,\"journal\":{\"name\":\"Journal of Nondestructive Evaluation\",\"volume\":\"44 3\",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s10921-025-01220-x.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Nondestructive Evaluation\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10921-025-01220-x\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, CHARACTERIZATION & TESTING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Nondestructive Evaluation","FirstCategoryId":"88","ListUrlMain":"https://link.springer.com/article/10.1007/s10921-025-01220-x","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, CHARACTERIZATION & TESTING","Score":null,"Total":0}
Immersive Inspection: Intuitive Material Analysis using X-Ray Computed Tomography Data in AR
Material analyses based on X-ray computed tomography (XCT) imaging are typically conducted away from scanning facilities, in separate office environments on 2D displays. This separation hinders on-site analysis, and due to the lack of spatial representation, limits the effective exploration of the material structure. We present a novel augmented reality (AR) framework enabling in-situ visualization of non-destructive testing (NDT) data spatially registered with real specimens. Our approach facilitates comprehensive exploration of primary and secondary XCT data, enabling researchers to inspect material properties onsite and in-place. Coupling immersive visualization techniques with real physical objects allows for highly intuitive workflows in material analysis and inspection, which enables the identification of anomalies and accelerates informed decision making. The AR framework offers automatic material recognition, hands-free workflows and embodied interaction with physical samples, generating an engaging analytical experience. A case study on fiber-reinforced polymer datasets was used to validate the AR framework and its new workflow. Expert evaluations revealed significant improvements in spatial data comprehension and more natural interaction compared to conventional analysis systems. This study demonstrates the potential of immersive AR technologies to enhance industrial materials analysis, providing preliminary insights for integrating such immersive approaches.
期刊介绍:
Journal of Nondestructive Evaluation provides a forum for the broad range of scientific and engineering activities involved in developing a quantitative nondestructive evaluation (NDE) capability. This interdisciplinary journal publishes papers on the development of new equipment, analyses, and approaches to nondestructive measurements.