Dissertations / Theses on the topic 'Surface defects'
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1
Clarke, Alasdair Daniel Francis. "Modelling visual search for surface defects." Thesis, Heriot-Watt University, 2010. http://hdl.handle.net/10399/2351.
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Much work has been done on developing algorithms for automated surface defect detection. However, comparisons between these models and human perception are rarely carried out. This thesis aims to investigate how well human observers can nd defects in textured surfaces, over a wide range of task di culties. Stimuli for experiments will be generated using texture synthesis methods and human search strategies will be captured by use of an eye tracker. Two di erent modelling approaches will be explored. A computational LNL-based model will be developed and compared to human performance in terms of the number of xations required to find the target. Secondly, a stochastic simulation, based on empirical distributions of saccades, will be compared to human search strategies.
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Williams, M. D. "Rail surface geometry defects and track settlement /." Title page, table of contents and introduction only, 1994. http://web4.library.adelaide.edu.au/theses/09ENS/09ensw725.pdf.
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Vyas, Shyam. "Simulation of ceria : bulk and surface defects." Thesis, Imperial College London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398294.
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MARQUES, MARCOS ALEXANDRE. "CHARACTERIZATION OF SURFACE DEFECTS ROLLED STEEL PRODUCTS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2003. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=4394@1.
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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIORO estudo teve por objetivo investigar o mecanismo de formação de trincas superficiais na direção longitudinal de laminação em barras do aço 1538 DH adotado na fabricação de componentes para a indústria automobilística. Tem-se conseguido alguns avanços no entendimento dos mecanismos de trincamento de produtos laminados, porém tais avanços não permitem, até o presente momento, a eliminação total do problema, o que vem causando o sucateamento de um expressivo percentual de produtos siderúrgicos. No escopo deste trabalho chegou-se a características microestruturais do material que sugerem as causas do trincamento durante o processo de laminação e, para tal, realizou-se o mapeamento das trincas, análises por microscopia ótica, classificação das inclusões, caracterizações por microscopia eletrônica de varredura e EDS, difração de raios-X, ensaios de tração, ensaios de dureza e microdureza, bem como simulação de ciclos térmicos. Os resultados destas análises indicaram que a nucleação e posterior propagação das trincas podem estar relacionadas à presença de precipitados de segunda fase em regiões interdendríticas, o que causaria a fragilização do contorno de grão durante laminação a quente.
The purpose of this study was to investigate the cracking mechanism with regard to longitudinal surface cracks in rolled 1538 DH steel bars used for the automotive industry. Although some advances have been achieved concerning the understanding of the cracking mechanism, the problem is not yet totally eliminated and still causing the scraping of a significant percentage of steel products. In the course of this work it was possible to determine some microstructural characteristics of the material which may lead to cracking due to the rolling process. In this sense, it was necessary to carry out an experimental procedure that included crack mapping, optical microscopy, classification of the inclusions, scanning electron microscopy, EDS analysis, X- ray diffraction, tensile testing, hardness and microhardness evaluation as well as thermal cycle simulations. The results seem to suggest that the crack nucleation and crack propagation are related to the presence of interdendritic second phase particles which induce to grain boundary embrittlement during hot rolling.
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Fan, Yichao. "The analysis of surface defects using the ultrasonic Rayleigh surface wave." Thesis, University of Warwick, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.495017.
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Surface defects, such as rolling contact fatigue (RCF) cracking, can be a difficult class of surface defects for existing on-line non-destructive testing techniques to detect and size accurately at high speed. Gauge corner cracking on the running surface of the railway track is a type of RCF defect. There are economic and safety benefits to have an accurate, fast and reliable NDT technique to detect such defects. The EMAT pitch-catch ultrasonic testing technique, using the Rayleigh surface wave developed at the laser ultrasound group, has been shown to be able to detect and size surface defects. The pitch-catch geometry also allows this technique to be used at high speed, for on-line NDT applications.
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Cregan, Robert Fraser. "Defects on the free surface of superfluid helium." Thesis, University of Exeter, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.261949.
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Shanmugham, Chetiyar Krishna Kumar, and Venkata Sri Sai Sumanth Galla. "Measurement of Surface Defects in 3D Printed Models." Thesis, Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-32487.
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The ease of manufacturing using additive manufacturing (3D-Printing) reduces the overall production cost compared with the traditional manufacturing techniques. Because of the benefits of 3D printing technologies, it is proposed to be used in manufacturing of different products. But there are some flaws that are causing significant effect on 3D printed models which degrades the quality of the product. Hence in order to handle these defects, different measurement techniques are needed to quantify the defects that are seen on the surface of 3D-printed models. In our study there are two experimental setups. Experimental setup one was made to find out the proper coating timing to enable measurement using two good samples without defects in different colors blue and red with same material. Different 2D and 3D parameters were used for the surface measurements are collected and noted for further research. The Defective samples are measured using the state of the art equipment at Halmstad University. Experimental setup two was made to prepare the defective samples and measure the samples. The results obtained assisted to quantify the surface defects seen in the samples. This thesis studies some of the different methods that can be implemented to measure the surface defects on the 3D printed models. A little study on the various defects formed on the 3D printed models and what are the causes for the defects on the products were performed. The results suggest different method for the defects to be measured in both industrial and home or small scale office applications.
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Choi, Jae-Boong. "Plastic collapse of circumferential surface defects in pipeline materials." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq22194.pdf.
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Kamal, Alm Hajer. "Interfacial Adhesion Failure : Impact on print-coating surface defects." Doctoral thesis, KTH, Fiber- och polymerteknologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-194166.
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The aim of this work was to develop a solid knowledge on formulation effects controlling offset ink-paper coating adhesion and to identify key factors of the coating and printing process affecting it. Focus lay on comprehending the impact of pigment dispersant on ink-paper coating adhesion and ultimately on the print quality of offset prints. The work covers laboratory studies, a pilot coating trial designed to produce coated material with a span in surface chemistry and structure, and an industrial offset printing trial. The lab scale studies quantified ink-paper coating adhesion failure during ink setting with a developed laboratory procedure based on the Ink-Surface Interaction Tester (ISIT) and image analysis. Additional polyacrylate dispersant resulted in slower ink setting and reduced ink-paper coating adhesion, with a dependence on its state of salt neutralisation and cation exchange, mainly in the presence of moisture/liquid water. The industrial printing trial on pilot coated papers was designed to study how these laboratory findings affected full scale offset print quality. These trials confirmed the dispersant-sensitive effect on ink-paper coating adhesion, especially at high water feeds. Evaluation of prints from the printing trial resulted in two fundamentally different types of ink adhesion failure being identified. The first type being traditional ink refusal, and the second type being a novel mechanism referred to as ink-lift-off adhesion failure. Ink-lift-off adhesion failure occurs when ink is initially deposited on the paper but then lifted off in a subsequent print unit. In this work, ink adhesion failure by this ink-lift-off mechanism was observed to occur more often than failure due to ink refusal. Print quality evaluation of the industrial prints suggested that water induced mottle was caused by a combination of ink-surface adhesion failure, creating white spots on the print, together with variation in ink layer thickness due to emulsified ink.QC 20161019
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Thomas, Sarah A. "EPR study of intrinsic near surface defects in SiC." Birmingham, Ala. : University of Alabama at Birmingham, 2009. https://www.mhsl.uab.edu/dt/2009m/thomas.pdf.
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Pi, Xiaodong. "Positron annihilation spectroscopy of sub-surface defects in semiconductors." Thesis, University of Bath, 2003. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.426150.
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Palanisamy, Suresh, and n/a. "Ultrasonic inspection of gas porosity defects in aluminium die castings." Swinburne University of Technology. Industrial Research Institute Swinburne, 2006. http://adt.lib.swin.edu.au./public/adt-VSWT20060828.103450.
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This thesis documents a PhD research program undertaken at Swinburne
University of Technology between the years 2000 and 2004. The research was
funded by the Cooperative Research Centre for Cast Metals Manufacturing and was
undertaken in collaboration with Nissan Casting Plant Australia Pty Ltd and the Ford
Motor Company Australia Limited. This thesis reports on the investigation of the
possibility of using an ultrasonic sensing-based, non-destructive testing system to
detect gas porosity defects in aluminium die casting parts with rough surfaces. The
initial intention was to develop a procedure to obtain ultrasonic signals with the
maximum possible amplitude from defects within the rough surface areas of the
castings. A further intention was to identify defects with the application of a suitable
signal processing technique to the raw ultrasonic signal. The literature review has
indicated that ultrasonic techniques have the potential to be used to detect subsurface
defects in castings. The possibility of classifying very weak ultrasonic signals
obtained from rough surface sections of castings through a neural network approach
was also mentioned in the literature. An extensive search of the literature has
indicated that ultrasonic sensing techniques have not been successfully used to detect
sub-surface defects in aluminium die castings with rough surfaces.
Ultrasonic inspection of castings is difficult due to the influence of
microstructural variations, surface roughness and the complex shape of castings. The
design of the experimental set-up used is also critical in developing a proper
inspection procedure. The experimental set-up of an A-scan ultrasonic inspection rig
used in the research is described in this thesis. Calibration of the apparatus used in
the inspection rig was carried out to ensure the reliability and repeatability of the
results. This thesis describes the procedure used to determine a suitable frequency
range for the inspection of CA313 aluminium alloy castings and detecting porosity
defects while accommodating material variations within the part. The results
obtained from ultrasonic immersion testing indicated that focused probes operating at
frequencies between 5 MHz and 10 MHz are best suited for the inspection of
castings with surface roughness Ra values varying between 50 [micro milli] and 100 [micro milli]. For
the purpose of validating the proposed inspection methodology, gas porosity defects
were simulated through side-drilled holes in the in-gate section of selected sample
castings. Castings with actual porosity defects were also used in this research.
One of the conclusions of this research was that it was extremely difficult to
detect defects in castings with surface roughness above 125 [micro milli]. Once the ultrasonic
signal data was obtained from the sample aluminium die castings with different
surface roughness values ranging from 5 [micro milli] to 150 [micro milli] signal analysis was carried
out. Signal feature extraction was achieved using Fast Fourier Transforms (FFT),
Principal Component Analysis (PCA) and Wavelet Transforms (WT) prior to passing
the ultrasonic signals into a neural network for defect classification. MATLAB tools
were used for neural network and signal pre-processing analysis. The results
indicated that poor classification (less than 75%) was achieved with the WT, PCA
and combination of FFT/PCA and WT/PCA pre-processing techniques for rough
surface signals. However, the classification of the signals pre-processed with the
combination of WT/FFT, FFT/WT and FFT/WT/PCA classifiers provided much
better classification of more than 90% for smooth surface signals and 78% to 84%
for rough surface signals. The results obtained from ultrasonic testing of castings
with both real and simulated defects were validated with X-ray analysis of the
sample castings. The results obtained from this research encourage deeper
investigation of the detection and characterisation of sub-surface defects in castings
at the as-cast stage. Implications for the industrial application of these findings are
discussed and directions for further research presented in this thesis.
13
Clough, A. R. "A study on the near-field interactions of ultrasonic surface waves with surface-breaking defects." Thesis, University of Warwick, 2013. http://wrap.warwick.ac.uk/58643/.
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This thesis is concerned with the detection of surface-breaking defects, such as stress corrosion cracking, using an ultrasonic scanning approach in which a laser source and detector are scanned over the near-field of a defect. Large increases in the amplitude and frequency content of an incident ultrasonic wave are present when either the source or the detector is very close to the defect, leading to a phenomenon known as ultrasonic near-field enhancement. The extent of the ultrasonic enhancement varies with defect characteristics such as defect depth and angle to the surface. Ultrasonic enhancement is observed in both experiment and finite element simulations using Rayleigh waves for both scanning laser detection and scanning laser source methods. The near-field enhancement is shown to vary as a function of the angle of the defect to the horizontal for Rayleigh wave enhancements, allowing the positioning and characterisation of artificial angled defects that are similar to rolling contact fatigue defects in railtrack. The mechanisms behind the near-field enhancement of Rayleigh waves at angled defects are identified, and this aids in the understanding of the behaviour of ultrasound as it interacts with surface-breaking defects. Ultrasonic enhancements are also reported to be present in individual Lamb wave modes for interactions with artificial open-mouthed defects in thin plates, which are similar to the open end of stress corrosion defects. The mechanisms behind both the scanning laser detection and scanning laser source enhancements are identified and used to explain the variation in the enhancement as a function of increasing defect severity. Positioning of these defects is also achieved by identification of the enhancement location. Finally, the scanning laser technique is applied to real stress-driven defects, and both scanning approaches are shown to be capable of detecting partially-closed defects in a variety of sample geometries. The position, geometric alignment and an estimate of the defect depth are obtained for real defects in thin plates, pipework sections and in irregularly shaped engine components.
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Dandu, Naveen Kumar. "Effect of Surface Ligands and Surface Defects on the Electronic and Optical Properties of Quantum Dots." Diss., North Dakota State University, 2016. http://hdl.handle.net/10365/25913.
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Quantum dots (QDs) have drawn a special attention since recent past due to their properties such as broad range absorption ability, size tunable narrow emission, high extinction coefficients, and charge carriers ability. Nonetheless, imbalanced surface passivation/defects leads to the appearance of surface trap states inside the band gap, affecting both radiative and non-radiative dynamics. Experimentally, it is difficult to explore the effect of surface states as they are optically inactive. However, computations provide valuable insights to these characteristics. We performed calculations using density functional theory (DFT) and time-dependent DFT (TDDFT) to provide our insights to such effects. Firstly, we performed DFT studies to understand the effect of QD- ligand interactions on their photophysical properties. Our studies on thiols passivated CdSe QDs showed that passivation of their surface by equilibrium concentration of neutral thiols and negatively charged thiolates is essential to achieve photoluminescence (PL) enhancement. Additionally, we investigated the effect of surface defects on photophysical properties of silicon QDs. Our results showed that defects introduce mid gap states inside band-gap. Absorption spectra showed the appearance of dark/semi-dark states at the first energy band, proving that the surface states quench PL efficiency in QDs. Secondly, we studied the effect of QD-QD interactions on their optoelectronic properties. In collaboration with the experimental group from Prof. Hobbies’ lab, we studied interactions between defective and non-defective QDs. Calculated Forster Resonance Energy Transfer rates suggest that all the trap states in a defective QD would be filled by the excited electrons from the non-defective QD and thus emission happens from the highest bright energy state. We proposed this as the reason for the experimental observation of the increased on-time blinking and overall enhancement of PL in these QDs. Furthermore, in collaboration with experimentalists from Los-Alamos National Lab, we have provided our insights into the chemical engineering of self-assembling of PbSe QDs into (100) directed 2D nanoplates. Our surface energy calculations on the oriented attachments revealed that 2D nanoplates grown in (100) are more feasible than 3D quantum dots. Overall, our calculations not only supported the experimental findings, but also provided solutions to questions raised by experimentalists.Department of Energy (DOE) CAREER: DE-SC008446
Center for Computationally Assisted Science and Technology (CCAST)
15
Koprnicky, Miroslav. "Towards a Versatile System for the Visual Recognition of Surface Defects." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/888.
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Automated visual inspection is an emerging multi-disciplinary field with many challenges; it combines different aspects of computer vision, pattern recognition, automation, and control systems. There does not exist a large body of work dedicated to the design of generalized visual inspection systems; that is, those that might easily be made applicable to different product types. This is an important oversight, in that many improvements in design and implementation times, as well as costs, might be realized with a system that could easily be made to function in different production environments. This thesis proposes a framework for generalizing and automating the design of the defect classification stage of an automated visual inspection system. It involves using an expandable set of features which are optimized along with the classifier operating on them in order to adapt to the application at hand. The particular implementation explored involves optimizing the feature set in disjoint sets logically grouped by feature type to keep search spaces reasonable. Operator input is kept at a minimum throughout this customization process, since it is limited only to those cases in which the existing feature library cannot adequately delineate the classes at hand, at which time new features (or pools) may have to be introduced by an engineer with experience in the domain.
Two novel methods are put forward which fit well within this framework: cluster-space and hybrid-space classifiers. They are compared in a series of tests against both standard benchmark classifiers, as well as mean and majority vote multi-classifiers, on feature sets comprised of just the logical feature subsets, as well as the entire feature sets formed by their union. The proposed classifiers as well as the benchmarks are optimized with both a progressive combinatorial approach and with an genetic algorithm. Experimentation was performed on true colour industrial lumber defect images, as well as binary hand-written digits.
Based on the experiments conducted in this work, it was found that the sequentially optimized multi hybrid-space methods are capable of matching the performances of the benchmark classifiers on the lumber data, with the exception of the mean-rule multi-classifiers, which dominated most experiments by approximately 3% in classification accuracy. The genetic algorithm optimized hybrid-space multi-classifier achieved best performance however; an accuracy of 79. 2%.
The numeral dataset results were less promising; the proposed methods could not equal benchmark performance. This is probably because the numeral feature-sets were much more conducive to good class separation, with standard benchmark accuracies approaching 95% not uncommon. This indicates that the cluster-space transform inherent to the proposed methods appear to be most useful in highly dependant or confusing feature-spaces, a hypothesis supported by the outstanding performance of the single hybrid-space classifier in the difficult texture feature subspace: 42. 6% accuracy, a 6% increase over the best benchmark performance.
The generalized framework proposed appears promising, because classifier performance over feature sets formed by the union of independently optimized feature subsets regularly met and exceeded those classifiers operating on feature sets formed by the optimization of the feature set in its entirety. This finding corroborates earlier work with similar results [3, 9], and is an aspect of pattern recognition that should be examined further.
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Ibrahem, Mohammed A. "Multiwavelength photoconductivity of ZnO nanoparticles based on surface defects and plasmonics." Thesis, University of Hull, 2017. http://hydra.hull.ac.uk/resources/hull:16599.
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ZnO is distinguished as the semiconductor of choice in a variety of applications such as in optoelectronics and photodetectors owing to its superior light sensitivity, the ease of synthesis in a wide range of nanostructure forms and its tuneable optical and electrical properties. Herein, ZnO photoconductivity is investigated for two purposes; firstly, to assess device stability with different preparation conditions and environments and secondly, to improve and extend photodetection of ZnO into the visible and near-infrared by stimulating surface defects and plasmonics effect. Persistent photoconductivity resulting from UV irradiation of ZnO NP films is highly affected not only by oxygen adsorption but also by other organic species and water in atmospheric air. The stability of ZnO photodetector is found to be enhanced in terms of current magnitude and sustainable photocurrent cycles when the device is prepared, annealed and tested in a nitrogen environment. A noticeable difference is identified in the ZnO NP surface composition, represented by surface organic complexes when the film is prepared and annealed in air compared to nitrogen. The aforementioned species are found to be removed efficiently in oxidized fabrication environment such as in air while partially decomposed in nitrogen. This enables the ZnO surface to build new organic species and surface carbonates by electrochemical reaction with atmospheric CO2 leading to promote electrically active defects surface states. Narrow-band photoconductivity, with a spectral width of 0.16 eV, is obtained by irradiating ZnO NP films using green light. A new model involving electron transfer from deep defects to discrete shallow donors is introduced to explain the narrow spectrum and the exponential form of the current rise and decay transients. The green photocurrent responsivity can be enhanced by storage in air and this correlates with the formation of carbonate surface species by the capture of carbon dioxide during storage. We successfully demonstrated a solution-processed ZnO NP photodetector using a low-cost and scalable photolithographic approach to fabricate dual (ultraviolet and green) and single (ultraviolet only) wavelength detecting ZnO pixels on the same substrate using the same mask. We also show that the plasmonic effect can be used to extend the photoconductivity of ZnO NPs into the deep red/infrared spectral region utilizing gold nanoislands as a light absorber and source of hot electrons in a vertical device configuration involving PEDOT: PSS.
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Chaiworawitkul, Sakda 1977. "Detection of surface defects in infrastructure using wavelets and neural networks." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/84310.
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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2002.Includes bibliographical references (p. [225]-[228]).
by Sakda Chaiworawitkul.
M.Eng.
18
Beglitis, N. "First-principles studies of surface defects of model metal-oxide semiconductors." Thesis, University College London (University of London), 2011. http://discovery.ucl.ac.uk/1324515/.
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In this thesis, three different model metal-oxide semiconductor systems will be discussed. First, the impact of hydroxyl vacancies, OHvac, on the geometry, electronic structure, and mechanical properties of single-walled aluminosilicate, (Al2SiO7H4)N, and aluminogermanate, (Al2GeO7H4)36, nanotubes is investigated. It is found that, with the exception of one OHvac localised on the outer wall of the (Al2GeO7H4)36 tube, these defects induce occupied and empty states in the band gap. Those states are found to be highly localised both in energy and in real space. Different magnetisation states are also found, depending on both the chemical composition and the specific side with respect to the tube cavity. The focus of the thesis then shifts to one of the most important and well-studied metaloxide surfaces, the rutile TiO2(110) surface. The reactivity of the surface is revisited, in view of the discrepancy between theory and experiment on the interaction between molecular oxygen and surface hydroxyls. This discrepancy is resolved by proposing that excess charge, associated with the oxygen vacancy and originating from Ti interstitials, is present on the surface. This surface charge opens new reaction channels not theoretically possible otherwise. The study utilises hybrid Density Functional Theory (DFT) calculations and Scanning Tunneling Microscopy (STM) simulations to provide evidence for the proposed surface charging. The last part of the thesis focuses on another surface of TiO2, the (011) surface. TiO2(011) has recently attracted attention due owing to its reported high photocatalytic activity. Several proposed structures of the surface are inconsistent with each other. Recent developments, based on Surface X-Ray Diffraction (SXRD) data and DFT simulations, now agree on a new structure. In this part a review of the various structures is provided and further evidence is given on the validity of the new proposal by providing further insight on the appearance of the surface on the STM.
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Hu, Yazhe. "Degenerate Near-planar Road Surface 3D Reconstruction and Automatic Defects Detection." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/98671.
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This dissertation presents an approach to reconstruct degenerate near-planar road surface in three-dimensional (3D) while automatically detect road defects. Three techniques are developed in this dissertation to establish the proposed approach. The first technique is proposed to reconstruct the degenerate near-planar road surface into 3D from one camera. Unlike the traditional Structure from Motion (SfM) technique which has the degeneracy issue for near-planar object 3D reconstruction, the uniqueness of the proposed technique lies in the use of near-planar characteristics of surfaces in the 3D reconstruction process, which solves the degenerate road surface reconstruction problem using only two images. Following the accuracy-enhanced 3D reconstructed road surface, the second technique automatically detects and estimates road surface defects. As the 3D surface is inversely solved from 2D road images, the detection is achieved by jointly identifying irregularities from the 3D road surfaces and the corresponding image information, while clustering road defects and obstacles using a mean-shift algorithm with flat kernel to estimate the depth, size, and location of the defects. To enhance the physics-driven automatic detection reliability, the third technique proposes and incorporates a self-supervised learning structure with data-driven Convolutional Neural Networks (CNN). Different from supervised learning approaches which need labeled training images, the road anomaly detection network is trained by road surface images that are automatically labeled based on the reconstructed 3D surface information. In order to collect clear road surface images on the public road, a road surface monitoring system is designed and integrated for the road surface image capturing and visualization. The proposed approach is evaluated in both simulated environment and through real-world experiments. The parametric study of the proposed approach shows the small error of the 3D road surface reconstruction influenced by different variables such as the image noise, camera orientation, and the vertical movement of the camera in a controlled simulation environment. The comparison with traditional SfM technique and the numerical results of the proposed reconstruction using real-world road surface images then indicate that the proposed approach effectively reconstructs high quality near-planar road surface while automatically detects road defects with high precision, accuracy, and recall rates without the degenerate issue.Doctor of Philosophy
Road is one of the key infrastructures for ground transportation. A good road surface condition can benefit mainly on three aspects: 1. Avoiding the potential traffic accident caused by road surface defects, such as potholes. 2. Reducing the damage to the vehicle initiated by the bad road surface condition. 3. Improving the driving and riding comfort on a healthy road surface. With all the benefits mentioned above, it is important to examine and check the road surface quality frequently and efficiently to make sure that the road surface is in a healthy condition. In order to detect any road surface defects on public road in time, this dissertation proposes three techniques to tackle the road surface defects detection problem: First, a near-planar road surface three-dimensional (3D) reconstruction technique is proposed. Unlike traditional 3D reconstruction technique, the proposed technique solves the degenerate issue for road surface 3D reconstruction from two images. The degenerate issue appears when the object reconstructed has near-planar surfaces. Second, after getting the accuracy-enhanced 3D road surface reconstruction, this dissertation proposes an automatic defects detection technique using both the 3D reconstructed road surface and the road surface image information. Although physics-based detection using 3D reconstruction and 2D images are reliable and explainable, it needs more time to process these data. To speed up the road surface defects detection task, the third contribution is a technique that proposes a self-supervised learning structure with data-driven Convolutional Neural Networks (CNN). Different from traditional neural network-based detection techniques, the proposed combines the 3D road information with the CNN output to jointly determine the road surface defects region. All the proposed techniques are evaluated using both the simulation and real-world experiments. Results show the efficacy and efficiency of the proposed techniques in this dissertation.
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LORENZON, MONICA. "ROLE OF NONRADIATIVE SURFACE DEFECTS ON EXCITON RECOMBINATION PROCESSES IN SEMICONDUCTOR COLLOIDAL NANOSTRUCTURES." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2018. http://hdl.handle.net/10281/199095.
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Durante la mia tesi di dottorato mi sono occupata dello studio spettroscopico di nanocristalli colloidali di semiconduttore e in particolare della correlazione tra le loro superfici e la fotofisica, che ho studiato per mezzo di spettroelettrochimica (SEC) e spettroscopia ottica in atmosfera controllata. Più precisamente, ho studiato e modellizzato il comportamento di diversi tipi di nanocristalli sottoponendoli a variazioni controllate delle condizioni ossidanti/riducenti dell’ambiente che li circonda, con l’obiettivo di implementarne l’uso in sensori ottici di ossigeno.
L’elevato rapporto superficie-volume tipico dei nanocristalli fa sì che la loro fotoluminescenza sia fortemente influenzata da un’ampia distribuzione di stati introdotti da difetti superficiali. Un portatore catturato da una trappola in superficie, infatti, non è più disponibile per la ricombinazione radiativa, e abbassa la resa quantica del nanocristallo. Tramite SEC, si può applicare una differenza di potenziale elettrochimico (EC) a un sottile film di nanocristalli depositati su un substrato trasparente e conduttivo. La fotolumiscenza del campione viene eccitata e raccolta sia in continua sia temporalmente risolta tramite appositi rivelatori. L’applicazione di una differenza di potenziale EC negativo corrisponde ad aumentare il livello di Fermi del nanocristallo, riempiendone gradualmente i difetti superficiali e attivando l’intrappolamento di lacune. La fotoluminescenza che ne risulta dipende dall’effetto dominante tra lo spegnimento della stessa dovuto all’intrappolamento di lacune e l’aumento derivante dalla soppressione dell’intrappolamento di elettroni. Per ciascun materiale ho effettuato misure di SEC ed esperimenti in atmosfera controllata, per arrivare alla realizzazione di diversi tipi di sensori ottici di ossigeno (Pressure Sensitive Paints, PSPs), usati per monitorare il flusso di ossigeno nei pressi di superfici complesse o miniaturizzate. Tipicamente consistono in un mezzo poroso in cui è disperso un cromoforo organico, la cui emissione cambia in modo inversamente proporzionale alla pressione di ossigeno. Ho utilizzato nanocristalli di perovskite (cesio-piombo-bromo, CsPbBr3) per realizzare un’alternativa completamente inorganica alle PSP tradizionali, basate su un aumento di segnale sotto pressione ridotta. Questo approccio però non è ottimale in applicazioni in cui è necessario rilevare grandi quantità di ossigeno (a pressione ambientale, per esempio). Un avanzamento in questo senso è fornito dalla PSP ‘inversa’ che ho realizzato tramite nanoplatelet di seleniuro di cadmio (CdSe), che diversamente dai materiali tradizionali per PSP sono in grado di illuminarsi maggiormente, invece che di spegnersi, in presenza di ossigeno. Nonostante il vantaggio offerto dal materiale a comportamento inverso, sia le PSP inverse sia quelle tradizionali si basano su una misura radiometrica di intensità luminosa, la quale però può cambiare anche in seguito a variazioni di temperatura, o degradazione indotta da UV, il che comporta la necessità di complesse procedure di calibrazione. Un miglioramento importante che ho introdotto nel corso del mio dottorato è rappresentato dall’impiego di nanocristalli bi-emissivi core/shell di seleniuro di cadmio/solfuro di cadmio (CdSe/CdS), in grado di sostenere contemporaneamente eccitoni di core e di shell, la cui ricombinazione radiativa porta a fotoluminescenza a due colori (rosso e verde) anche con basse potenze di eccitazione. É importante notare che i due canali emissivi presentano una risposta opposta all’ossigeno, il che mi ha permesso di realizzare una PSP raziometrica e intrinsecamente calibrata, con elevata sensibilità sia a livello di ensemble sia di singola particella.The main research theme of my PhD has been the spectroscopic investigation of colloidal semiconductor nanocrystals (NCs), with a focus on the correlation between their surfaces and their photophysics, and was conducted by means of spectroelectrochemistry (SEC) and optical spectroscopy under controlled atmosphere. Specifically, I aimed to understand and model the NCs behavior in a changing oxidative/reducting environment, with the ultimate goal to implement their use as active material in optical oxygen pressure sensors. The high surface-to-volume ratio typical of NCs causes their photoluminescence (PL) efficiency to be strongly affected by a broad distribution of surface defect states. If captured by a surface trap, a photogenerated electron (or hole) becomes unavailable for the radiative recombination, thus lowering the overall PL efficiency of the NCs. By means of SEC, an electrochemical (EC) potential can be applied to a thin film of NCs deposited onto a transparent and conductive substrate, whose PL is excited and collected via dedicated instruments for either continuous or time-resolved measurements. The application of a negative EC potential corresponds to raising the Fermi level of the NCs, thus gradually filling the surface defects and activating their hole-trapping capability. The PL intensity is thus determined by the competition between the quenching effect of hole withdrawal and the brightening effect of suppressed electron trapping. For each material system I performed side-by-side SEC measurements and spectroscopic experiments under controlled atmosphere, and eventually demonstrated different types of optical oxygen pressure sensors, also called pressure-sensitive paints (PSPs), i.e, all-optical probes for monitoring oxygen flows in the vicinity of complex or miniaturized surfaces. They typically consist in a porous binder embedding an oxygen sensitive chromophore, whose PL intensity changes accordingly to the oxygen partial pressure. By employing cesium lead bromide (CsPbBr3) perovskite NCs, I realized an all-inorganic alternative to traditional organic PSPs, based on the increase of their PL intensity under reduced oxygen pressure. This approach relies on the disappearance of the signal in presence of oxygen, which means it may not represent the best approach when high oxygen concentrations (for instance, at atmospheric pressure) need to be detected. In this thesis, I demonstrated how to overcome this issue by realizing a novel-concept, inorganic ‘reverse’ PSP, with cadmium selenide (CdSe) nanoplatelets (NPLs) as active material, since their PL intensity increases with the oxygen concentration. Although the SEC and optical measurements under controlled atmosphere allowed me to understand and model the unusual benefit of an oxidative environment on CdSe NPLs, the PSPs based on them share with the perovskite-based sensors the major drawback of providing a radiometric oxygen detection only, that is, the measurement solely relies on a change in the PL intensity of the chromophore. The PL, however, can also change as a result of a temperature variation or UV-induced degradation. In my work, I introduced a significant improvement by employing dual-emitting, core/shell cadmium selenide/cadmium sulfide (CdSe/CdS) NCs that are capable of simultaneously sustaining core and shell excitons, whose radiative recombination leads to two-color (red and green) luminescence under low-intensity power excitation. Importantly, the two emissive channels exhibit opposite responses to the oxygen pressure, which allowed me to realize an intrinsically calibrated ratiometric PSP whose sensitivity is significantly enhanced with respect to traditional reference-sensor pairs, both in ensemble and at the single particle level.
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Chondronasios, Apostolos. "Investigation of surface defects for extruded aluminium profiles using pattern recognition techniques." Thesis, University of Portsmouth, 2015. https://researchportal.port.ac.uk/portal/en/theses/investigation-of-surface-defects-for-extruded-aluminium-profiles-using-pattern-recognition-techniques(31e4e51b-3238-4e43-ab02-f7e8d0a00ec1).html.
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This research investigates detection and classification of surface defects in extruded aluminium profiles in order to replace the traditional eye inspection which is still the method widely used today. Through an extensive literature review it is evident that extruded aluminium surface is not investigated properly, while similar industrial products such as copper strips or rolled steel have attracted more interest. An experimental machine vision system is used to capture images from surfaces of extruded aluminium profiles. Extensive feature selection is investigated and appropriate statistical features from a novel technique based on Gradient-Only Co-occurrence Matrices are used to detect and classify defects. The methodology created in this research, makes use of the Sobel edge detector to obtain the gradient magnitude of the image and is followed by the extraction of statistical texture measures from the gradient, after a transformation of the gradient values. Comparisons are made between the statistical features extracted from the original image (Gray-Level Co-occurrence Matrix) and those extracted from the gradient magnitude using a novel approach (Gradient-Only Co-occurrence Matrix). The features extracted from the image processing are classified by feed-forward artificial neural networks. Experiments were conducted for a three class and a four class case study, with the first consisting of Good Surface, Blisters and Scratches, and the second introducing Die Lines to the classes of the first case study. The artificial neural network training is tested using different combinations of statistical features with different topologies. Features are compared individually and grouped, showing better classification accuracy for the novel technique (98.9%) compared to research standard methodology of gray-level co-occurrence matrices (55.9%).
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Yang, Jiannan. "Time domain models of wheel/rail interaction taking account of surface defects." Thesis, University of Southampton, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.586162.
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A time domain wheel/rail interaction model in the vertical direction is developed taking account of surface defects. This model consists of a wheel moving over a finite element track model with a detailed non-Hertzian contact model. This numerical non-Hertzian contact model is either used for roughness pre-processing or is directly applied in combination with dynamic interaction calculations at each time step as the wheel moves along the rail. A non-reflecting boundary condition for the finite length track model is developed using a damped tapered tip. It is shown that the modal size of the track model is reduced by applying this damped tapered tip compared to traditional boundary conditions. The time domain wheel/rail interaction model is validated against field measurements from SNCF, in terms of rolling and impact noise predictions. Detailed roughness profiles are considered as the excitation by employing the non-Hertzian contact model. A big improvement is achieved at high frequencies in terms of rail vibration prediction, compared to a Hertzian contact model in combination with pre-processed roughness, by directly applying the non-Hertzian contact model for a wheelflat impact. The characteristics of the impact vibration due to a wheel flat are studied using a simple mass-spring representation of the track system. The frequency domain characteristics of the coupled system, assuming a linear contact spring, are found to be well related to the features of time domain simulations with a nonlinear spring due to the fact that a wheel flat irregularity has a relatively flat spectrum of the roughness. It is shown that the rail acts as a dynamic absorber during impact and the peak impact force is at its minimum when the rail absorbing effect is maximised. The predictions of rolling vibration are in deviations from the measurements. The possible errors are studied and suggesting these might be due to operational error of rail roughness measurements.
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Pratiwada, Chaitanya. "High Fidelity Detection of Defects in Polymer Films Using Surface-Modified Nanoparticles." University of Akron / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=akron1345586565.
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Chevtchenko, Serguei Aleksandrovich. "DEFECTS IN GaN: AN EXPERIMENTAL STUDY." VCU Scholars Compass, 2007. http://scholarscompass.vcu.edu/etd_retro/72.
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This work examines extended, point, and surface defects in GaN by means of electric force microscopy, photoluminescence and deep-level transient spectroscopy. Modeling of the surface band bending, its origin, and the effects of fabrication processing steps are discussed in the first part of the dissertation. Experimental results indicate that spontaneous polarization does not play a predominant role in GaN band bending. An increase of surface band bending due to annealing and etching was observed, while passivation did not produce changes. However, passivation did reduce reverse-bias leakage current by one to two orders of magnitude in GaN Schottky diodes. The optical properties of GaN were found to be sensitive to fabrication processing steps, most likely due to changes in the total density of surface states.The second part of this dissertation concerns the reduction of extended defects and associated deep levels in layers of GaN grown on different templates. Templates employing a low temperature GaN nucleation layer, epitaxial lateral overgrowth, and SiNx nanonetwork are compared in terms of deep level concentrations in the resulting GaN films. The concentrations of two types of traps, A (Ec-ET ~ 0.54-0.58 eV) and B (Ec-ET ~ 0.20-0.24 eV), were the highest for the sample with a low temperature nucleation layer and lowest for a sample with a 6 min SiNx deposition time. We surmise that the defects responsible for the dominant trap A are located along dislocation lines and form clusters.In the last part we investigate the piezoelectric and ferroelectric properties of PZT in Pb(Zr, Ti)O3(PZT)/GaN structures, and the effects of interface states. Sol-gel derived thin PZT films on GaN and Pt/Ti/SiO2/Si surfaces were studied by piezoresponse force microscopy (PFM), where quantitative characterization of piezoelectric properties of PZT films was performed. Superior piezoelectric properties of PZT/GaN/sapphire structures as compared to PZT/ Pt/Ti/SiO2/Si structures were observed and explained by a different preferred orientation of PZT. Despite the possible existence of a strong depolarization field at the PZT/GaN interface, we confirm with PFM the presence of a remanent polarization in PZT/GaN/sapphire structures.
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Chen, Haiyan. "Probing Defects and Electronic Processes on Gadolinia-doped Ceria Surfaces Using Electron Stimulated Desorption." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/10427.
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Probing Defects and Electronic Processes on Gadolinia-doped Ceria Surfaces Using Electron Stimulated Desorption
Haiyan Chen
133 Pages
Directed by Professor Thomas M. Orlando
Polycrystalline gadolinia-doped ceria (GDC) has been widely investigated as a promising low temperature solid oxide fuel cell (SOFC) electrolyte and as part of composite electrodes. In this thesis, electron stimulated desorption (ESD) has been used to probe the defect related electronic properties of GDC surfaces and the interactions of water and molecular oxygen with these surfaces.
In particular, the electron irradiation induced surface charging of GDC has been found to be dependent on the incident electron energy: negative at lower energy and positive at higher energy. Trapping of electrons and holes by the gadolinium aggregated, oxygen vacancy rich grain boundaries has been considered as the origin of surface charging. Depending on the sample treatment, there can be various defects, hydroxyl groups, chemically adsorbed water molecules, or water dimers on GDC surfaces. Water and molecular oxygen interact primarily with defect sites.
Systematic investigations of electron stimulated O+ desorption have yielded activation energies relevant to oxygen vacancy production on ceria surfaces, and to surface positive charge dissipation related to ionic conduction of GDC. Highly efficient electron stimulated O+ desorption from GDC surfaces has been attributed to the lowered charge density on oxygen ions coordinated with oxygen vacancy clusters and thus may be used as a probe for surface defect types.
Electron stimulated desorption of O2+ from GDC surfaces during molecular oxygen adsorption has shown the ability of ESD to detect chemically adsorbed O2. The velocity distributions of O2+ can be used to probe intermediate adsorption species such as O2, as well as the positive charge of the surface.
Overall, this thesis has demonstrated that ESD can provide important information on the kinetics and dynamics of surface charging, charge transport, adsorption and reactions occurring at defective insulating metal oxides materials. The abilities to probe the defects and their roles in surface processes make ESD a valuable technique for surface chemistry and catalysis studies.
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Mirjana, Filipovic. "Evolution of artificial defects during shape rolling." Licentiate thesis, Högskolan Dalarna, Materialvetenskap, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:du-5215.
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Very often defects are present in rolled products. For wire rods, defects are very deleterious since the wire rods are generally used directly in various applications. For this reason, the market nowadays requires wire rods to be completely defect-free. Any wire with defects must be rejected as scrap which is very costly for the production mill. Thus, it is very important to study the formation and evolution of defects during wire rod rolling in order to better understand and minimize the problem, at the same time improving quality of the wire rods and reducing production costs. The present work is focused on the evolution of artificial defects during rolling. Longitudinal surface defects are studied during shape rolling of an AISI M2 high speed steel and a longitudinal central inner defect is studied in an AISI 304L austenitic stainless steel during ultra-high-speed wire rod rolling. Experimental studies are carried out by rolling short rods prepared with arteficial defects. The evolution of the defects is characterised and compared to numerical analyses. The comparison shows that surface defects generally reduce quicker in the experiments than predicted by the simulations whereas a good agreement is generally obtained for the central defect.
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Ganapathiraman, Subburengan. "QUANTIFICATION OF SURFACE DEFECTS USING PRIMARY HIGHLIGHT IN DIFFUSE ANGLE GRAY SCALE IMAGES." UKnowledge, 2005. http://uknowledge.uky.edu/gradschool_theses/348.
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The thesis presented is an effort to gather all possible information of one particular type of common paint defect the seed defect, from gray scale images of highly specular painted surface. The proposed approach in the thesis utilizes a white light source to illuminate the surface and utilizes a camera to capture its gray scale image at different diffused angles. While attempting to explain the physics of highlight formation in terms of location on the surface of a seed defect, the thesis also extends to utilize this information from gray scale images to accurately predict the parameters of seed defects including the height, size and position in real time. Since the primary highlight in a gray scale image is more defined, contrary to the past researches on diffuse angle images that use both primary / seed highlight and mirror highlight to estimate height of the seed, this thesis formulates a theory of highlight translation and estimates the height of seed based on primary / seed highlight. The other common type of surface defect - crater defect, is also addressed in the thesis.
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Li, Kaile. "Defects at surface and interface of crystals : theoretical and x-ray scattering analysis /." free to MU campus, to others for purchase, 2002. http://wwwlib.umi.com/cr/mo/fullcit?p3074422.
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GNANAPRAKASAM, PRADEEP. "CHARACTERIZATION OF SEED DEFECTS IN HIGHLY SPECULAR SMOOTH COATED SURFACES." UKnowledge, 2004. http://uknowledge.uky.edu/gradschool_theses/318.
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Many smooth, highly specular coatings such as automotive paints are subjected to considerable performance demands as the customer expectations for appearance of coatings are continually increasing. Therefore it is vital to develop robust methods to monitor surface quality online. An automated visual assessment of specular coated surface that would not only provide a cost effective and reliable solution to the industries but also facilitate the implementation of a real-time feedback loop. The scope of this thesis is a subset of the inspection technology that facilitates real-time close loop control of the surface quality and concentrates on one common surface defect the seed defect. This machine vision system design utilizes surface reflectance models as a rational basis. Using a single high-contrast image the height of the seed defect is computed; the result is obtained rapidly and is reasonably accurate approximation of the actual height.
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Zhu, Zhenhua. "Column recogniton and defects/damage properties retrieval for rapid infrastructure assessment and rehabilitation using machine vision." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/44768.
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No matter how inspection techniques have been advanced, manual visual inspection is currently still the first and fundamental step in assessing civil infrastructure. If no sign of deterioration has been spotted in manual inspection, any future inspection actions is not necessary to take. However, manual inspection has been identified with several limitations including the qualitative nature of inspection results, the time-consuming inspection process, and the heavy reliance on inspectors' and/or engineers' experience. In order to overcome these limitations, automated visual inspection systems have been proposed to enhance and/or replicate the manual inspection process. A number of image processing methods have been developed in detecting defects (i.e. coating rusts) and damage (i.e. cracks) on civil infrastructure. Their effectiveness has been verified in inspecting structures, such as bridges, underground pipes, and tunnels.
Although existing methods are effective in finding defects and damage from digital images, missing two important links limits their application for rapid infrastructure assessment and rehabilitation. The first link is the correlation between the defects/damage and the structural members that the defects/damage lie on. The second link is the relationship between the defects/damage and their impacts on the structural members.
The purpose of this research is to investigate the way of establishing these two links. It is focused on the retrieval of critical structural members and defects/damage information from images/videos, and then the utilization of this information for automated and rapid assessment and rehabilitation of civil infrastructure. Specifically, a combination of techniques from the areas of visual pattern recognition, digital filtering, and machine vision have been used in order to develop a set of methods for concrete column recognition, crack properties retrieval, and air pockets and discoloration detection and evaluation. The methods proposed in this research were implemented in a Microsoft Visual Studio environment, and tested on the real images/videos of concrete structures inflicted with cracks, air pockets and discoloration. The test results indicated that the methods could automatically recognize concrete columns, correctly measure the properties of the cracks in a crack map, and accurately evaluate the impacts of air pockets and discoloration on the visual quality of concrete surfaces.
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Jensen, Stephen C. "The Role of Interstitials and Surface Defects on Oxidation and Reduction Reactions on Titania." Thesis, Harvard University, 2013. http://dissertations.umi.com/gsas.harvard:10768.
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This thesis focuses on understanding the influence of defect sites in titanium dioxide that drive many types of thermal and photochemical reactions. Two of the most common defects in vacuum are titanium interstitials and oxygen vacancies. Molecular oxygen fills oxygen vacancies and creates oxygen adatoms. We broadly investigate reduction and oxidation reactions of oxygenates driven by titanium interstitials and oxygen adatoms. First, we focus on the thermal chemistry of oxygen adatoms with butyrophenone and find that it reacts with the adatoms to form a strongly bound complex. The large difference in mobility between complexed and uncomplexed butyrophenone, and the corrugated nature of the \(TiO_2(110)\) surface plane, allows a confined one-dimensional gas to persist, which is characterized by scanning tunneling microscopy (STM). Next, we focus on the reductive coupling of benzaldehyde to stilbene that is driven by titanium interstitials. The diolate intermediate of the reaction is identified by STM and the thermodynamic preference of molecular oxygen to interact with titanium interstitials is exploited to selectively reverse the benzaldehyde diolate intermediates. Additionally, we investigate the photo-oxidative coupling of methanol to methyl formate, the photo-oxidation of butyrophenone and the photo-stability of benzoate. Finally, we identify a water splitting mechanism on reduced titania that creates oxygen adatoms. We demonstrate that the photo-generated oxygen adatoms thermally react with titanium interstitials to make TiOx islands and drive the photo-oxidation of formaldehyde and butyrophenone. Methods used include temperature programmed reaction spectroscopy, STM, and density functional theory.Chemistry and Chemical Biology
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Cedergren, Pettersson André. "Bismuth(III)iodide for photovoltaic applications : Minimization of surface defects for maximization of efficiency." Thesis, Uppsala universitet, Fysikalisk kemi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-297750.
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Danner, Kyle Ricardo. "Utilizing automated inspection to identify surface quality defects within the automotive body assembly process." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/126951.
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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 111-112).
Nissan relies on inspectors to perform manual inspections in order to ensure vehicles are produced with a high-quality surface finish. These inspections occur throughout the vehicle assembly process and are meant to identify surface quality defects as well as determine at which major step in the vehicle assembly process the defect originated. An issue of uncertainty arises because inspectors routinely identify defects on completed vehicles and then deem the Body Assembly Shop, an upstream process, as responsible for creating the defect. However, inspectors in the Body Assembly Shop have already evaluated the vehicle and guaranteed it to be defect free. This indicates that inspectors in the Body Assembly Shop are failing to identify defects or inspectors at the end of the process are misidentifying the vehicle assembly process in which the defect originated.
The objective of this project is to determine the effectiveness of an automated solution for inspecting vehicles in the Body Assembly Shop. Our approach was to first understand the basic physics underlying the chosen automated solution, the ZEISS ABIS II sensor, in order to understand its limitations when identifying a defect. We tested the ABIS II sensor on a replication of the Nissan production line in order to determine the sensor performance in identifying defects relative to Nissan requirements. A scaled-down version of testing was also completed on the actual Nissan production line so as to determine the impact on performance due to variation induced by the moving line and vehicle assembly processes. Overall, we found that the ABIS II sensor is able to identify surface quality defects consistent with the characteristics described by Nissan's standards. In fact, the lower limit of defect size identified by the ABIS II sensor is smaller than Nissan typically refers to as a defect.
Additionally, we identified changes to Nissan's existing processes as well as new feedback loops that can be used to validate or refute defect responsibility assignments. Changes to existing processes include letting surface quality defects pass through the painting process in order to fine tune the automated inspection limits in the Body Assembly Shop. We also identified the possibility of using automated surface quality inspection data to validate or refute the defect responsibility assignment that is determined at the end of the assembly process. Using downstream manual inspections to fine tune the automated inspection in an iterative manner can lead to effectively shortening the closed loop feedback process so that defects are contained and repaired in the Body Assembly Shop.
by Kyle Ricardo Danner.
M.B.A.
S.M.
M.B.A. Massachusetts Institute of Technology, Sloan School of Management
S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering
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Sangghaleh, Ali. "Surface Loading on and Internal Defects in Layered Magneto-Electro-Elastic Materials and Structures." University of Akron / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=akron1415290055.
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Filipovic, Mirjana. "Evolution of artificial defects during shape rolling." Licentiate thesis, Stockholm : Division of Mechanical Metallurgy, Department of Material Science and Engineering, Industrial Engineering and Management, Royal Institute of Technology, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4350.
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Asel, Thaddeus J. "Nanoscale Characterization of Defects in Complex Oxides and Germanane." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1523982077791833.
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Bainbridge, Ian Frank. "The influence of molten metal surface properties on the formation of surface defects on vertical direct chill cast aluminium alloy products /." [St. Lucia, Qld.], 2005. http://adt.library.uq.edu.au/public/adt-QU20060116.141809/index.html.
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Höglund, Andreas. "Electronic Structure Calculations of Point Defects in Semiconductors." Doctoral thesis, Uppsala universitet, Fysiska institutionen, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7926.
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In this thesis point defects in semiconductors are studied by electronic structure calculations. Results are presented for the stability and equilibrium concentrations of native defects in GaP, InP, InAs, and InSb, for the entire range of doping conditions and stoichiometry. The native defects are also studied on the (110) surfaces of InP, InAs, and InSb. Comparing the relative stability at the surface and in the bulk, it is concluded that the defects have a tendency to migrate to the surface. It is found that the cation vacancy is not stable, but decomposes into an anion antisite-anion vacancy complex. The surface charge accumulation in InAs is explained by complementary intrinsic doping by native defects and extrinsic doping by residual hydrogen. A technical investigation of the supercell treatment of defects is performed, testing existing correction schemes and suggesting a more reliable alternative. It is shown that the defect level of [2VCu-IIICu] in the solarcell-material CuIn1-xGaxSe2 leads to a smaller band gap of the ordered defect γ-phase, which possibly explains why the maximal efficiency for CuIn1-xGaxSe2 has been found for x=0.3 and not for x=0.6, as expected from the band gap of the α-phase. It is found that Zn diffuses via the kick-out mechanism in InP and GaP with activation energies of 1.60 eV and 2.49 eV, respectively. Explanations are found for the tendency of Zn to accumulate at pn-junctions in InP and to why a relatively low fraction of Zn is found on substitutional sites in InP. Finally, it is shown that the equilibrium solubility of dopants in semiconductors can be increased significantly by strategic alloying. This is shown to be due to the local stress in the material, and the solubility in an alloy can in fact be much higher than in either of the constituting elements. The equilibrium solubility of Zn in Ga0.9In0.1P is for example five orders of magnitude larger than in GaP or InP.
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Glatz, Bernhard Alexander [Verfasser], and Andreas [Akademischer Betreuer] Fery. "Surface wrinkling of elastic supported membranes : Controlling defects and upscaling / Bernhard Alexander Glatz ; Betreuer: Andreas Fery." Bayreuth : Universität Bayreuth, 2020. http://d-nb.info/1204997470/34.
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Novák, Martin. "KONTROLA POVRCHOVÝCH VAD BROUŠENÝCH POVRCHŮ." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2008. http://www.nusl.cz/ntk/nusl-227941.
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This diploma is focused on analyse existing method usable for detection surface defects of grindling surface. Also suggests and practically testing new method for detection surface defects of grindling surface
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Werner, Kristin. "On the Role of Oxygen Vacancies in the Surface Chemistry of Ceria (CeO2)." Doctoral thesis, Humboldt-Universität zu Berlin, 2019. http://dx.doi.org/10.18452/20496.
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Ceroxid (CeO2) wurde in den letzten Jahren als Katalysator für die Hydrierung von Alkinen zu Alkenen entdeckt und hat als solcher großes wissenschaftliches Interesse geweckt. Um weitere Einblicke in die Funktion von CeO2 in der Reaktion zu gewinnen, beschäftigt sich diese Arbeit mit der Adsorption von H2, CO2 und Propin, sowie mit der Interaktion von Hydroxylgruppen und Propin auf CeO2(111)-Oberflächen. Ein besonderer Fokus liegt dabei auf der Rolle von Sauerstoffleerstellen.In recent years, ceria (CeO2) has attracted much scientific interest due to its activity as a catalyst in the selective hydrogenation of alkynes to alkenes. To gain further insights into the role of CeO2 in propyne hydrogenation, this thesis explores the fundamental processes of H2, CO2, and propyne adsorption, as well as the interaction of hydroxyls and propyne on well-defined CeO2(111) surfaces. A special emphasis thereby lies on the role of oxygen (O) vacancies in these processes.
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Duan, Jianglan. "Physical and computational models of free surface related defects in low-pressure die-cast aluminum alloy wheels." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/38862.
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The difference of die filling, which can be characterized by the free surface flow behavior, has a strong influence on the quality of casting components. In the case of cast aluminum alloy wheels, an undesired filling pattern with excessive turbulence can cause portions of the surface oxide film to be entrained within the bulk liquid resulting in defects such as cosmetic paint-pops, hot tears, porosity and rim-leaks.
To investigate the influence of die filling on defect formation in low-pressure die-cast aluminum wheels, a water analogue physical model was built, instrumented and tested to simulate the free surface behavior during die filling of a low-pressure die-cast (LPDC) wheel. The physical model contains a transparent planar die section which was manufactured out of the geometry of a production die, and an automatic pressure control system that achieves liquid feeding conditions similar to the industrial process. A set of die filling tests with different venting conditions was carried out to explore the role of venting on the free surface behavior of water and to produce data for validation of a computational model. The computational model was developed, based on the commercial computational fluid dynamics code ANSYS CFX, for the purposes of predicting the flow conditions during die filling, providing qualitative and quantitative flow information that are otherwise not possible to obtain through experimental measurement, and identifying key features that influences the flow during die filling at a lower cost of time and labor.
Comparison between the experimental and numerical data has shown that the computational model was able to qualitatively reproduce the flow behavior observed in the water model in the conditions tested. Both the experimental and the model results indicate that the entrainment of surface oxide films and air bubbles could occur at the outboard rim flange during the filling of the flange, below the free surface of the returning waves in the spoke and at the junction of the hub and the spoke during the filling of the hub. Venting conditions have been proved crucial and the importance of vent design in commercial die design was highlighted.
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Yong-Hong-Chen and 陳永宏. "Image Recognition of Surface Defects." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/19127699192033788056.
Full textAbstract:
碩士國立中興大學
物理學系所
103
We used scanning tunneling microscope(STM) to take surface structure image.We also can use Vienna Ab-initio Simulation Package (VASP) simulate surface structure, respectively. The image of graphene surface and Si(111) -7 × 7 taken from STM and simulated by VASP are reistrated and identified in this work.
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LAI, JIA-WEI, and 賴嘉偉. "Automatic Inspection Of Surface Defects For Glass." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/71841947360358966325.
Full textAbstract:
碩士聖約翰科技大學
自動化及機電整合研究所
100
This paper proposed a nondestructive detection method to inspect surface defects of glass. The automatic optic inspection (AOI) technologies integrated automation mechanism, plc, machine-vision and human-machine interface. The article studies two topics: 1.The glasses transported by conveyed belt for capturing images using CCD camera. The defect standard is judged by the pixel sizes and then the complete glasses were sent to the classification area. The AOI system not only shortened inspection time, but also reduce the manufacturing cost. 2.The Back-Propagation Neuro Network is used to verify the inspection system accuracy.
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Da-Chin, Lee, and 李大青. "Automatic Vision Inspection for IC Leadframe Surface Defects." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/00055427666593926645.
Full textAbstract:
碩士華梵大學
機電工程研究所
87
At present, the IC leadframes products are still inspected and the defects of the bad leadframes are classified by QA with human vision piece by piece , then the statistic data of defects are passed to the manufacturing department to adjust the manufacture process in the semi-conductor industry. The QA inspection process is time and costs wasted. This paper is divided into three parts: First, the specification of the leadframe defects for industry are concluded and leadframes are inspected by self-maded optical relay system with the cylinder infinite principles. The second, three methods are proposed for Go, No-Go inspection which are included: (1) the etching scale inspected with area formula principle (2) Ag misalign inspected with central coordinates alignment method (3) the short and defects of leadframe inspected with template matching method. The third, the Fast Fourier Transform frequency spectrum and correlation method are proposed for pits, foreign material, Ag sludge, nodule, rust classification. Keywords: leadframe、defect inspection、defect classification、Fast Fourier transform frequency spectrum、correlation
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Lin, Chia-Tsung, and 林洽琮. "Vision-based Detection of Steel Billet Surface Defects." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/70303522988153904329.
Full textAbstract:
碩士國立雲林科技大學
資訊工程系
103
Automatic inspection techniques have been widely employed to achieve high productivity while ensuring high-quality products in steelmaking industry.In this paper, a vision-based detection framework for automatically detecting different types of steel billet surface defects is proposed. The defects considered in this study include scratches, corner cracks, sponge cracks, slivers, and roll marks and without blocking artifacts, respectively. In the proposed framework, to improve the quality of image acquisition for billet surface, two preprocessing techniques, i.e., automatic identification of ROI (region of interest) and HDR (high dynamic range)-based image enhancement techniques, are proposed. Then, DWT (discrete wavelet transform)-based image feature is extracted from the image to be detected and fused with the other two extracted local features based on variance and illumination to identify each defect on the billet surface. Experimental results have verified the feasibility of the proposed method.
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CHEN, GUAN-SHOU, and 陳冠守. "Steel Surface Defects Detection based on Deep Learning." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/j7x799.
Full textAbstract:
碩士國立中正大學
資訊工程研究所
106
Surface defects detection plays a significant role in quality enhancement in steel manufacturing. However, manual inspection of steel surface slows down the entire process and time consuming. Currently, many methods had been proposed for automatic defect detection on hot-rolled steel surface. These methods usually follow two steps: pre-processing and segmentation. The pre-processing step is to overcome the uneven illumination of images and the segmentation step is to generate the binary map to identify defect. This kind of methods highly depend on feature selection approaches, but the defect features are usually not easy to obtain. In this thesis, we propose an automatic steel surface defects detection method based on deep learning to replace traditional way to image processing. The deep learning models will be evaluated for defect detection. The experimental results show that the proposed method can detect steel surface defects more effectively and accurately than the traditional methods, and this approach can be also applied to other industrial applications.
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Chu, Chien-Cheng, and 朱建政. "The Research on the BGA Surface Defects Detecting System." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/27776357187759659286.
Full textAbstract:
碩士元智大學
工業工程與管理學系
91
In the current manufacturing environment, a company still needs to have a faster and a more accurate ways to inspect a Ball Grid Array (BGA) surface defects. Traditionally, the BGA inspection was using gray-level images. However, the background, conduct paths and pads have very similar gray-levels that cannot easy be distinguished. The objectives of the research are: (1) Use some shape and uniformity features without making pattern matching for detecting BGA surface defects. (2) Use color image information instead of gray scales for the inspection. (3) Improve the speed and effectiveness of the inspection system. The traditional process of the image enhancement is to select a suitable color mode and then to proceed on the enhancement. The research proposed a method that to use the gamma correction method to replace the tradition process for image enhancement with the expectations of having better results and faster speeds. Because gamma correction corrects the three color bands (i.e., RGB), it could better separate the image between the high and low contrasts. And it could get the better results in dividing the image into background and foreground by using the Gamma correction and the R color band. As a result, the proposed method can improve the contrast value about 52.09%. Finally, the research uses the eigenvalues of the shape and uniformity to detect the defects. It could find almost all the defects. In using the traditionally enhancement method with a 640* 480 pixels image to do a completely defects detecting needs 1 sec. However, to use the proposed gamma correction method to do the same, needs only 0.3 sec. This research demonstrates the effectiveness of using gamma correction method for separating an image background from its foreground. And the developed method could detect the BGA surface defects without using pattern matching technique that required extensive alignment in both hardware and software.
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Chen, Shun-Ming, and 陳舜民. "Au-induced Defects on Si(100)-2×1 Surface." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/cp63j4.
Full textAbstract:
碩士國立中正大學
物理學系暨研究所
102
By using scanning tunneling microscope (STM), we have observed three types of defects on clean , well-ordered Si(100)-2×1 surfaces . These defects are compared with those structures of a surface where a small amount of Au has been deposited. Such comparison gives us a way of identifying structures induced by Au deposition. Au atom have been deposited on the Si(100)-21 surface at 600C with coverages ranging between x.x and x.x ML. After deposition, missing dimer defects have been observed and, as the Au coverage increases, those missing dimer defects tend to form missing dimer lines in the direction perpendicular to the dimer rows. After depositing x.x ML Au, the surface transforms into a (82) reconstruction.
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Chin, Kuo-ming, and 秦國銘. "An Auto-detecting System for Surface Defects on Connectors." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/15136333166234472158.
Full textAbstract:
碩士朝陽科技大學
資訊工程系碩士班
96
Exploiting computer vision techniques, an auto-detecting system is developed for surface defects on connectors. The system hardware consists of a CCD (charge-coupled device) camera, a loop-shaped light-source, and an image capture board. Since the surface of connectors is made of stainless steel with high reflectance, it is difficult to locate the defects specifically. This problem is usually solved by applying extra light on the dark area. However, the reflection of the extra light might induce some detection errors. We classify the surface regions as some regions of interest (ROI) and ones that are not of interest (non-ROI) so as to accomplish real-time on-line diagnosis by image positioning and template recognition. Applied image processing techniques include edge detection, image segmentation, binary images, and template recognition. According to the examination results, the system effectively detects the surface defects. The Examination time is 32ms per sample.