{"title":"利用动态 X 射线计算机显微层析技术在实验室条件下自动追踪三维粒子的方法","authors":"Judith Marie Undine Siebert, Stefan Odenbach","doi":"10.1007/s11242-024-02086-9","DOIUrl":null,"url":null,"abstract":"<div><p>This paper presents a method for particle tracing in laboratory X-ray micro-computed tomography (<i>µ</i>CT) using an adjusted Random Sample Consensus (RANSAC) algorithm combined with least squares ellipse fitting (LSF). For method testing, a setup for the investigation of deep bed filtration (DBF) has been used as an example of a complex process that can be elucidated with such a method. Particle tracking with tomography systems requires high-temporal resolution which can only be achieved with synchrotron radiation computer tomography. Therefore, in this work, it has been demonstrated that instead of particle tracking, particle tracing in opaque systems such as DBF can be performed in laboratory <i>µ</i>CT systems. To achieve particle tracing, dynamic <i>µ</i>CT scans with a duration between 30 and 110 s combined with an exposure time of 0.13 s/projection were executed and during the scan time the filtration was performed, causing parabola shaped motion artefacts. The developed method exploits the motion artefacts created by the particle motion during the scan. It could be shown that it is possible to trace particles in complex structures within only one 30 s scan. Furthermore, through trace length and time, it is possible to determine the average velocity. Whereby, the accuracy and limits depend on the particle size, particle velocity/data rate and the X-ray attenuation of particle and medium.</p></div>","PeriodicalId":804,"journal":{"name":"Transport in Porous Media","volume":"151 7","pages":"1607 - 1626"},"PeriodicalIF":2.7000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11242-024-02086-9.pdf","citationCount":"0","resultStr":"{\"title\":\"A Method for Automatic Three-Dimensional Particle Tracing Under Laboratory Conditions Using Dynamic X-Ray Computed Microtomography\",\"authors\":\"Judith Marie Undine Siebert, Stefan Odenbach\",\"doi\":\"10.1007/s11242-024-02086-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper presents a method for particle tracing in laboratory X-ray micro-computed tomography (<i>µ</i>CT) using an adjusted Random Sample Consensus (RANSAC) algorithm combined with least squares ellipse fitting (LSF). For method testing, a setup for the investigation of deep bed filtration (DBF) has been used as an example of a complex process that can be elucidated with such a method. Particle tracking with tomography systems requires high-temporal resolution which can only be achieved with synchrotron radiation computer tomography. Therefore, in this work, it has been demonstrated that instead of particle tracking, particle tracing in opaque systems such as DBF can be performed in laboratory <i>µ</i>CT systems. To achieve particle tracing, dynamic <i>µ</i>CT scans with a duration between 30 and 110 s combined with an exposure time of 0.13 s/projection were executed and during the scan time the filtration was performed, causing parabola shaped motion artefacts. The developed method exploits the motion artefacts created by the particle motion during the scan. It could be shown that it is possible to trace particles in complex structures within only one 30 s scan. Furthermore, through trace length and time, it is possible to determine the average velocity. Whereby, the accuracy and limits depend on the particle size, particle velocity/data rate and the X-ray attenuation of particle and medium.</p></div>\",\"PeriodicalId\":804,\"journal\":{\"name\":\"Transport in Porous Media\",\"volume\":\"151 7\",\"pages\":\"1607 - 1626\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s11242-024-02086-9.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transport in Porous Media\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s11242-024-02086-9\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transport in Porous Media","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s11242-024-02086-9","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
引用次数: 0
摘要
本文介绍了一种在实验室 X 射线显微计算机断层扫描(µCT)中使用调整随机样本共识(RANSAC)算法结合最小二乘椭圆拟合(LSF)进行粒子追踪的方法。在方法测试中,以深床过滤(DBF)的研究装置为例,说明了这种方法可以阐明的复杂过程。使用层析成像系统进行粒子跟踪需要高时间分辨率,而这只有同步辐射计算机层析成像才能实现。因此,在这项工作中,已经证明可以在实验室 µCT 系统中进行不透明系统(如 DBF)中的粒子追踪,而不是粒子追踪。为了实现粒子追踪,我们执行了持续时间在 30 到 110 秒之间的动态 µCT 扫描,曝光时间为 0.13 秒/投影,在扫描期间进行过滤,从而产生抛物线形状的运动伪影。所开发的方法利用了扫描过程中粒子运动产生的运动伪影。结果表明,只需一次 30 秒的扫描,就能对复杂结构中的粒子进行追踪。此外,通过跟踪长度和时间,还可以确定平均速度。因此,精度和限制取决于颗粒大小、颗粒速度/数据率以及颗粒和介质的 X 射线衰减。
A Method for Automatic Three-Dimensional Particle Tracing Under Laboratory Conditions Using Dynamic X-Ray Computed Microtomography
This paper presents a method for particle tracing in laboratory X-ray micro-computed tomography (µCT) using an adjusted Random Sample Consensus (RANSAC) algorithm combined with least squares ellipse fitting (LSF). For method testing, a setup for the investigation of deep bed filtration (DBF) has been used as an example of a complex process that can be elucidated with such a method. Particle tracking with tomography systems requires high-temporal resolution which can only be achieved with synchrotron radiation computer tomography. Therefore, in this work, it has been demonstrated that instead of particle tracking, particle tracing in opaque systems such as DBF can be performed in laboratory µCT systems. To achieve particle tracing, dynamic µCT scans with a duration between 30 and 110 s combined with an exposure time of 0.13 s/projection were executed and during the scan time the filtration was performed, causing parabola shaped motion artefacts. The developed method exploits the motion artefacts created by the particle motion during the scan. It could be shown that it is possible to trace particles in complex structures within only one 30 s scan. Furthermore, through trace length and time, it is possible to determine the average velocity. Whereby, the accuracy and limits depend on the particle size, particle velocity/data rate and the X-ray attenuation of particle and medium.
期刊介绍:
-Publishes original research on physical, chemical, and biological aspects of transport in porous media-
Papers on porous media research may originate in various areas of physics, chemistry, biology, natural or materials science, and engineering (chemical, civil, agricultural, petroleum, environmental, electrical, and mechanical engineering)-
Emphasizes theory, (numerical) modelling, laboratory work, and non-routine applications-
Publishes work of a fundamental nature, of interest to a wide readership, that provides novel insight into porous media processes-
Expanded in 2007 from 12 to 15 issues per year.
Transport in Porous Media publishes original research on physical and chemical aspects of transport phenomena in rigid and deformable porous media. These phenomena, occurring in single and multiphase flow in porous domains, can be governed by extensive quantities such as mass of a fluid phase, mass of component of a phase, momentum, or energy. Moreover, porous medium deformations can be induced by the transport phenomena, by chemical and electro-chemical activities such as swelling, or by external loading through forces and displacements. These porous media phenomena may be studied by researchers from various areas of physics, chemistry, biology, natural or materials science, and engineering (chemical, civil, agricultural, petroleum, environmental, electrical, and mechanical engineering).