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Optimised performance of industrial high resolution computerised tomography
Linköping University, Department of Mechanical Engineering, Engineering Materials. Linköping University, The Institute of Technology.
2000 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The purpose of non-descructive enluation (NDE) is to acquire knowledge of the investigated sample. Digital x-ray imaging techniques such as radiography or computerised tomography (CI) produce images of the interior of a sample. The obtained image quality determines the possibility of detecting sample, ·elated features, e.g. details and flaws. this thesis presents a method of optinllsing the performance of industrial X-ray equipment for the imaging task at issue in order to obtain images with high quality.

CT produces maps of the X-ray linear attenuation of the sample's interior. CT can produce two-dimensional cross-section images or three-dimensional images with volumetric information on the investigated sample. The image contrast and noise depend on both the investig-Ated sample and the equipment and settings used (X-ray tube potential, X-ray filtration, exposure time, etc.). Hence, it is vital to find the optimal equipment settings in order to obtain images of high quality.

To be able to mathematically optimise the image guality, it is necessary to have a model of the X-ray imaging system together with an appropriate measure of image quality. The optimisation is performed with a developed model for an X-ray image-intensifier-based radiography system. The model predicts the mean value and variance of the measured signal level in the collected radiographic images. The traditionally used measure of physical image guality is the signal-to-noise ratio (SNR). To calculate the signal-to-noise ratio, a well-defined detail (flaw) is required. It was found that maximising the SNR leads to ambiguities, the optimised settings found by maximising the SNR were dependent on the material in the detail. When CT is performed on irregular shaped samples containing density and compositional variations, it is difficult to define which SNR to use for optimisation. This difficulty is solved by the measures of physical image quality proposed here, the ratios geometry-sensitivity/ noise, density-sensitivity/noise, and mass attenuation-sensitivity/noise. With these measures, a meiliod is presented that finds the optimal eguipment settings, where no improvement can be made without worsening at least one other sensitivity/noise ratio.

This thesis includes modelling and verification of the sharpness of the CT system in terms of the modulation transfer function, MTF. Together with the limiting perception factor and the maximised SNR, the detectability limits for any specific contrasting detail in the centre of a cylindrical sample can be determined. It is also demonstrated that the model can be used to suppress beam hardening when collecting CT-data. When homogeneous samples are imaged, the model can in addition be used to make post-processing corrections for suppressing the beam hardening artefacts.

Wavelet-based local tomography has been found to produce images with good accuracy from projection data only from a small region in a sample. Tlus technique is demonstrated on thermal barrier coatings, which contain internal cracks. With optimised eguipment settings and geometrical magnification of a region in the sample, wavelet-based local tomography produced high-resolution images of excellent quality. The increased resolution reveals features in the microstructure that cannot be resolved wiili traditional CT. This technigue will be a useful tool for characterisation of the microstructure in advanced materials.

Place, publisher, year, edition, pages
Linköping: Linköpings universitet , 2000. , 34 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 659
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-30060Local ID: 15520ISBN: 91-7219-887-7 (print)OAI: oai:DiVA.org:liu-30060DiVA: diva2:250881
Public defence
2000-12-05, Sal C3, Linköpings universitet, Linköping, 10:15 (Swedish)
Opponent
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2013-02-14
List of papers
1. Modelling of an X-ray image-intensifier-based radiography system
Open this publication in new window or tab >>Modelling of an X-ray image-intensifier-based radiography system
1998 (English)In: Journal of X-Ray Science and Technology, ISSN 0895-3996, E-ISSN 1095-9114, Vol. 8, no 1, 31-50 p.Article in journal (Refereed) Published
Abstract [en]

A model will be proposed for predicting the expected value and variance of the measured signal-level in collected radiographic images obtained with an image-intensifier-based X-ray radiography system. The model parameters are determined from both theoretical and experimental data and incorporate all parameters that can be varied by the system operator, except CCD-camera readout rate. The proposed model predicts the expected value and variance of the grey-level in the output image with high accuracy. It is also shown that it is very important to compensate for the inhomogeneous pixel sensitivity when comparing the variance of the signal-level in a pixel from sequentially collected images with the variance determined in a single image.

Keyword
Image intensifier, X-ray radiography, modelling
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-20933 (URN)22388425 (PubMedID)
Available from: 2009-09-25 Created: 2009-09-25 Last updated: 2017-12-13
2. Optimised detail detectability in computerised tomography
Open this publication in new window or tab >>Optimised detail detectability in computerised tomography
1998 (English)In: Journal of X-Ray Science and Technology, ISSN 0895-3996, E-ISSN 1095-9114, Vol. 8, no 1, 51-73 p.Article in journal (Refereed) Published
Abstract [en]

It is of interest to know the minimum discernible detail size when performing non-destructive testing with high-resolution computerised tomography. But it is difficult to empirically find optimal parameter settings that maximise detectability for each individual imaging task. In this work a method to determine the optimal performance for a high-resolution computerised tomography system has been developed. It reveals the detectability limit for specific contrasting details in terms of imaged object diameter when the signal-to-noise ratio, SNRΔS,CT, between the contrasting detail and its surroundings has been maximised using optimal data collection parameter settings.

This work includes modelling and verification of the total unsharpness of the CT-system in terms of modulation transfer-function, MTF. Together with the limiting perception factor and maximised SNRΔproj in the CT projection data, the detectability limits for any specific contrasting detail are determined as a function of imaged object material and geometry. Maximised SNRΔproj was obtained by optimising the parameters: X-ray source tube potential, X-ray filter, exposure time and optical aperture. The importance of using optimal settings when performing CT-investigations, especially when investigating objects with large diameters, is demonstrated.

It was found that it is possible to predict the detectability for any specific contrasting detail. It was also discovered that the optimal settings for a given object diameter and material are dependent on the detail material. In some cases an improvement of the detail signal-to-noise-ratio was obtained by using a combination of X-ray filter materials. It was also found that SNRΔproj is very sensitive to the thickness of denser X-ray filter materials (higher atomic number and density).

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-88688 (URN)
Available from: 2013-02-14 Created: 2013-02-14 Last updated: 2017-12-06
3. Correction for beam hardening artefacts in computerised tomography
Open this publication in new window or tab >>Correction for beam hardening artefacts in computerised tomography
1998 (English)In: Journal of X-Ray Science and Technology, ISSN 0895-3996, E-ISSN 1095-9114, Vol. 8, no 1, 75-93 p.Article in journal (Refereed) Published
Abstract [en]

Conventional computerised tomography systems (CT) are usually equipped with polyenergetic X-ray sources, which prevents accurate density measurements because of the general CT-image artefact called beam hardening (BH). BH results in false gradients of the linear attenuation coefficient in the CT cross section images, indicating a non-existent density or composition gradient in the imaged object. A number of methods have been proposed to correct for, or limit the effect of, beam hardening. One of these is called linearisation of the CT-data, in which the polyenergetic CT-data are transformed to monoenergetic CT-data. This requires knowledge of the CT-data as a function of object thickness. Data points to derive this function are usually measured using a set of samples of different object material thicknesses at the imaging parameter settings used and fitted with a polynomial. However, the sample preparation makes this method tedious to use. In this work a simulation method has been developed, which can accurately simulate the polyenergetic CT-data for any arbitrary object material and thickness if a priori information of the object material density and composition exists. The simulation method requires detailed knowledge of the imaging system, that is, X-ray energy spectra, detector response and information transfer from detector to digitised data. Besides developing the simulation tool, it has been shown that one of the major difficulties with this BH-correction method is to accurately determine the curvature of the function representing the polyenergetic CT-data. Earlier proposed endorsements to fit a second-degree polynomial to the polyenergetic CT-data are not sufficient to describe its curvature, at least a polynomial of degree eight or higher is required. Here cubic-spine interpolation is used, which avoids the problem.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-88689 (URN)
Available from: 2013-02-14 Created: 2013-02-14 Last updated: 2017-12-06
4. Optimal conditions for X-ray imaging by mathematical simulation
Open this publication in new window or tab >>Optimal conditions for X-ray imaging by mathematical simulation
1999 (English)In: AIP Conference Proceedings 509 / [ed] Sarah Kallsen, Connie Nessa, Donald O. Thompson, Dale E. Chimenti, Linda Poore, 1999, 665-672 p.Conference paper, Published paper (Refereed)
Abstract [en]

Image quality strongly affects the detectability, which is the possibility to detect defects. To obtain maximum detectability it is necessary to conduct the testing with optimal equipment settings. In radiography and computerized tomography based on conventional poly-energetic x-rays, the optimal equipment settings depend on the imaging task. An imaging task is defined as testing of a specific object with a specific defect, defined by composition and geometry. However, the optimal equipment settings (e.g., x-ray tube potential, x-ray filtration and exposure time) are tedious to find experimentally. This is particularly true for industrial applications due to the wide range of imaging tasks. In this work, mathematical models of the image collection process for radiography and computerized tomography have been developed. The objective has been to develop techniques to aid the imaging operator to find optimal imaging parameters. With the models it is possible to find the optimal settings and to predict the detectability of defects in terms of its size as a function of imaged object diameter and these are formulated in terms of detectable detail—object diameter diagram. It is shown that the image quality is very sensitive with respect to the settings, with e.g., slightly non-optimal choice of x-ray filter thickness leading to a loss of image quality that cannot be compensated by varying the x-ray tube potential. Furthermore, non-optimal conditions are found to considerably reduce the detectability of defects, especially for large objects.

Keyword
nondestructive testing, X-ray imaging, radiography, computerised tomography, modelling, digital simulation, optical transfer function, optimisation, random noise, image processing
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-30136 (URN)10.1063/1.1306113 (DOI)15616 (Local ID)1-56396-930-0 (ISBN)15616 (Archive number)15616 (OAI)
Conference
Review of progress in quantative nondestructive evaluation, 25-30 July, Montreal, Canada
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2013-02-14
5. Computerised tomography with optimised sensitivity to physical variations in the sample
Open this publication in new window or tab >>Computerised tomography with optimised sensitivity to physical variations in the sample
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Digital X-ray imaging techniques such as radiography or computerised tomography produce images of the interior of a sample. It is difficult to empirically find equipment settings such that the obtained images arc of high quality. This work presents an optimisation procedure for finding the optimal equipment settings for the imaging task at issue. It includes a suggested procedure for finding the optimiscd equipment settings even when complex samples arc investigated. To be able to mathematically optimisc the image quality, it is necessary to have a model of the X-ray imaging system together with an appropriate measure of image quality. This work proposes the ratios geometry-sensitivity/noise, density-sensitivity/noise and mass attenuation sensitivity/noise as measures of the physical image quality. A mathematical model of the imaging system was used to calculate and predict the ratios. The model predictions agreed well with the measured values. It is shown that the geometry- and density-sensitivity/noise ratios can be related to the signal-to-noise ratio and the traditional thickness (contrast) sensitivity.

The weighted maximin method is used to obtain the optimal equipment settings. With the optimal settings, no improvement can be made without worsening at least one other sensitivity/noise ratio. It is demonstrated how the weights (penalties) can be selected to focus the sensitivity on different types of features in the investigated sample.

The optimisation procedure is demonstrated on thermal barrier coatings investigated with CT. Optimised and non-optimiscd settings were used in the investigation. By optimising the equipment settings, the sensitivity/noise ratios are increased with approximately 100% for the selected X-ray path. With the optimised settings, the obtained CT images are of better quality and more features in the microstructure can be observed.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-88697 (URN)
Available from: 2013-02-14 Created: 2013-02-14 Last updated: 2013-02-14
6. Optimised wavelet-based local tomography of thermal barrier coatings
Open this publication in new window or tab >>Optimised wavelet-based local tomography of thermal barrier coatings
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Optimised wavelet-based local tomography has been found to be a useful non-destructive evaluation tool for studying the microstructure in thermal barrier coatings. Two-dimensional wavelet-based local tomography produced high-resolution images of regions inside the investigated samples. The investigated samples were cur from two thermal shock tested jet engine burner cans. The inside of the burner cans was coated with a thick thermal barrier coating consisting of a top coating made of partially stabilised zirconia (PSZ) and a bond coating (BC) of NiCoCrAlY. The coatings were manufactured with plasma spraying with two different spraying parameters. This resulted in samples with and without a segmented crack network in the as-sprayed top coating.

The obtained wavelet-based local CT-imagcs of the investigated samples from the thermal shock tested burner cans reveal cracks and pores in the microstructure. The obtained pixel-sizes in the local CT-images were 4.0 μm and 3.1 μm respectively. Small or no improvements in resolution arc made when the pixel-size is in the vicintiy of the X-ray focal spot size, in this case 5 μm. A traditional CT-investigation, collecting global data that covers the whole cross-section of the sample, would have resulted in 2.6 and 6.8 times bigger pixel-sizes respectively. A CT-image reconstructed from global data would therefore not resolve all features seen in the wavelet-based local CT-images.

To obtain CT-images with a high image quality a mathematical optimisation procedure is used to find the optimal equipment settings for collecting the CT-data. The geometry-sensitivity/noise, density-sensitivity/noise and mass attenuation-sensitivity/noise ratios are maximised using the weighted minimax method. The sensitivity/noise ratios are calculated using a mathematical model of the X-ray imaging system. The image quality is improved if the sample completely shades the detector and optimised equipment settings for this case are used. The sensitivity/noise ratios in the local CT-investigation of one of the samples are increased with at least 20% compared to if air gaps would have been present.

A procedure to suppress ring artefacts in the reconstructed CT-images is presented. The procedure is found to give good results.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-88707 (URN)
Available from: 2013-02-14 Created: 2013-02-14 Last updated: 2013-02-14

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