The paper gives a survey of the upcoming use of X-ray computed tomography (CT) for dimensional quality control purposes: i.e. for traceable measurement of dimensions of technical (mechanical) components and for tolerance verification of such components. It describes the basic principles of CT metrology, putting emphasis on issues as accuracy, traceability to the unit of length (the meter) and measurement uncertainty. It provides a state of the art (anno 2011) and application examples, showing the aptitude of CT metrology to: (i) check internal dimensions that cannot be measured using traditional coordinate measuring machines and (ii) combine dimensional quality control with material quality control in one single quality inspection run.

Computed tomography for dimensional metrology

Industrial x-ray computed tomography (CT) scanners are used for non-contact dimensional measurement of small, fragile components and difficult-to-access internal features of castings and mouldings. However, the accuracy and repeatability of measurements are influenced by factors such as cone-beam system geometry, test object configuration, x-ray power, material and size of test object, detector characteristics and data analysis methods. An attempt is made in this work to understand the measurement errors of a CT scanner over the complete scan volume, taking into account only the errors in system geometry and the object configuration within the scanner. A cone-beam simulation model is developed with the radiographic image projection and reconstruction steps. A known amount of errors in geometrical parameters were introduced in the model to understand the effect of geometry of the cone-beam CT system on measurement accuracy for different positions, orientations and sizes of the test object. Simulation analysis shows that the geometrical parameters have a significant influence on the dimensional measurement at specific configurations of the test object. Finally, the importance of system alignment and estimation of correct parameters for accurate CT measurements is outlined based on the analysis.

http://iopscience.iop.org/article/10.1088/0957-0233/22/3/035105/pdf

Analysis of the effect of cone-beam geometry and test object configuration on the measurement accuracy of a computed tomography scanner used for dimensional measurement

http://manuscript.elsevier.com/S0007850622001275/pdf/S0007850622001275.pdf

Advances in the metrological traceability and performance of X-ray computed tomography

In industrial X-ray cone-beam computed tomography, the inspection of large-scale samples is important because of increasing demands on their quality and long-term mechanical resilience. Large-scale samples, for example made of aluminum or iron, are strongly scattering X-rays. Scattered radiation leads to artifacts such as cupping, streaks, and a reduction in contrast in the reconstructed CT-volume. We propose a scatter correction method based on sampling primary signals by employing a beam-hole array (BHA). In this indirect method, a scatter estimate is calculated by subtraction of the sampled primary signal from the total signal, the latter taken from an image where the BHA is absent. This technique is considered complementary to the better known beam-stop array (BSA) method. The two scatter estimation methods are compared here with respect to geometric effects, scatter-to-total ratio and practicability. Scatter estimation with the BHA method yields more accurate scatter estimates in off-centered regions, and a lower scatter-to-total ratio in critical image regions where the primary signal is very low. Scatter correction with the proposed BHA method is then applied to a ceramic specimen from power generation technologies. In the reconstructed CT volume, cupping almost completely vanishes and contrast is enhanced significantly.

Comparison between beam-stop and beam-hole array scatter correction techniques for industrial X-ray cone-beam CT

In the energy range of industrial cone-beam CT (a 450 kV X-ray tube is used), the detector scatter (veiling glare) turned out to be the most important source of secondary radiation for a digital imaging system working in the indirect conversion mode. It has been shown that the detector scatter drives the shape of the total image scatter. As a consequence, the latter may be characterized by an important high spatial frequency content questioning the hypothesis, frequently invoked in the scatter correction techniques, of a slowly varying scatter. We propose a beam stop array (BSA) based method for the evaluation/subtraction of the image scatter. The technique has the potential of simultaneously manage all sources of scattering radiation. It can be used in the high spatial frequency scatter case at the condition of opportunely selecting the BSA effective sampling step. It has been shown that the BSA approach can be also successfully combined with a beam hardening correction scheme based on the linearisation method. The work we present is supported by experimental measurements performed with two test objects at two different beam qualities: (i) 200 kV + 2.5 mm of Cu and (ii) 400 kV + 4 mm of Pb and 1 mm of Cd. The detector scatter represents about 36% and 65% of the total white field image for the two investigated beam qualities, respectively.

A beam stop based correction procedure for high spatial frequency scatter in industrial cone-beam X-ray CT

An X-ray computed tomography (CT) model based on the GEANT4 Monte Carlo code was developed for simulation of a cone-beam CT system for industrial applications. The full simulation of the X-ray tube, object, and area detector was considered. The model was validated through comparison with experimental measurements of different test objects. There is good agreement between the simulated and measured projections. To validate the model we reduced the beam aperture of the X-ray tube, using a source–collimator, to decrease the scattered radiation from the CT system structure and from the walls of the X-ray shielding room. The degradation of the image contrast using larger beam apertures is also shown. Thereafter, the CT model was used to calculate the spatial distribution and the magnitude of the scattered radiation from different objects. It has been assessed that the scatter-to-primary ratio (SPR) is below 5% for small aluminum objects (approx. 5 cm path length), and in the case of large aluminum objects (approx. 20 cm path length) it can reach up to a factor of 3 in the region corresponding to the maximum path length. Therefore, the scatter from the object significantly affects quantitative accuracy. The model was also used to evaluate the degradation of the image contrast due to the detector box. r 2007 Elsevier B.V. All rights reserved.

Monte Carlo simulations of a high-resolution X-ray CT system for industrial applications

Computed tomography (CT) is a very useful non-destructive testing technique in the industrial field, since it permits the detection of small inner defects in a reliable and accurate way. In order to get very good performance, in terms of image contrast and spatial resolution, the configuration of the tomography system has to be optimized carefully. Monte Carlo simulations can be very helpful for choosing different conditions and selecting the best configurations of a CT system. In this paper, we present a preliminary optimization of an industrial CT apparatus, obtained by means of Monte Carlo simulations. The system is composed of an X-ray tube, filtering and collimation devices, and a detector made of a scintillator coupled to a CCD camera. We focus our attention on large aluminum objects, such as motor heads, and investigate the contribution of the scattered radiation. Some options have been simulated, for reducing the scattering photons, thus improving the overall image quality.

Monte Carlo optimization of an industrial tomography system

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

M. Simon

Author Tools

Chat about Author

Papers

Monte Carlo simulations of a high-resolution X-ray CT system for industrial applications

Monte Carlo optimization of an industrial tomography system