Nowadays there is a strong demand for lighter vehicles in order to increase the pay load. Through this the specific fuel consumption is decreased, the amount of greenhouse gases is lowered and the transport economy improved. One possibility to optimize the weight is to make the components from high strength steels and join them by welding. Welding is the main joining method for fabrication of a large proportion of all engineering structures. Many components experience fatigue loading during all or part of their life time and welded connections are often the prime location of fatigue failure.Fatigue fracture in welded structures often initiates at the weld toe as aconsequence of large residual stresses and changes in geometry acting as stress concentrators. The objective of this research is to increase the understanding of the factors that control fatigue life in welded components made from very high strength steels with a yield strength of more than 800 MPa. In particular the influences of the local weld toe geometry (weld toe radius and angle) and residual stress on fatigue life have been studied. Residual stresses have been varied by welding with conventional as well as Low Transformation Temperature (LTT) filler materials. The three non-destructive techniques Weld Impression Analysis (WIA), Laser Scanning Profiling (LSP) and Structured Light Projection (SLP) have been applied to evaluate the weld toe geometry.Results suggest that all three methods could be used successfully to measure the weld toe radius and angle, but the obtained data are dependent on the evaluation procedure. WIA seems to be a suitable and economical choice when the aim is just finding the radius. However, SLP is a good method to fast obtain a threedimensional image of the weld profile, which also makes it more suitable for quality control in production. It was also found that the use of LTTconsumables increased fatigue life and that residual stress has a relatively larger influence than the weld toe geometry on fatigue strength of welded parts.

The inclusion of precision dairy farming technologies in dairy operations is an area of increasing research and industry direction. Machine vision based systems are suitable for the dairy environment as they do not inhibit workflow, are capable of continuous operation, and can be fully automated. The research of this dissertation developed and tested 3 machine vision based precision dairy farming technologies tailored to the latest generation of RGB+D cameras. The first system focused on testing various imaging approaches for the potential use of machine vision for automated dairy cow feed intake monitoring. The second system focused on monitoring the gradual change in body condition score (BCS) for 116 cows over a nearly 7 month period. Several proposed automated BCS systems have been previously developed by researchers, but none have monitored the gradual change in BCS for a duration of this magnitude. These gradual changes infer a great deal of beneficial and immediate information on the health condition of every individual cow being monitored. The third system focused on automated dairy cow feature detection using Haar cascade classifiers to detect anatomical features. These features included the tailhead, hips, and rear regions of the cow body. The features chosen were done so in order to aid machine vision applications in determining if and where a cow is present in an image or video frame. Once the cow has been detected, it must then be automatically identified in order to keep the system fully automated, which was also studied in a machine vision based approach in this research as a complimentary aspect to incorporate along with cow detection. Such systems have the potential to catch poor health conditions developing early on, aid in balancing the diet of the individual cow, and help farm management to better facilitate resources, monetary and otherwise, in an appropriate and efficient manner. Several different applications of this research are also discussed along with future directions for research, including the potential for additional automated precision dairy farming technologies, integrating many of these technologies into a unified system, and the use of alternative, potentially more robust machine vision cameras.

Cette thèse s'inscrit dans le cadre d'un projet national nommé SRDViand dont le but fut de développer un système robotisé pour le désossage et la découpe des animaux de boucherie. Afin de déterminer les trajectoires de découpe de manière intelligente, un système de lumière structurée a été développé. Il se réfère à des systèmes de vision qui utilisent des modèles de projection de lumière pour des tâches de reconstruction 3D. Afin d'obtenir les meilleurs résultats, la définition d'une nouvelle méthode d'étalonnage pour les systèmes de lumière structurée a été établie. Basé sur un large état de l'art et également sur la proposition d'une classification de ces méthodes, il a été proposé d'étalonner une paire caméra projecteur en utilisant l'asservissement visuel. La validité et les résultats de cette méthode ont été éprouvés sur la base de nombreux tests expérimentaux menés dans le cadre du projet SRDViand. Suite à l'élaboration de cette méthode, un prototype permettant la découpe des bovins a été réalisé. / This thesis is part of a national project named SRDViand whose aim was to develop a robotic system for the deboning and cutting of animals meat. To determine the cut paths, a structured light system has been developed. It refers to vision systems that use light projection models for 3D reconstruction tasks. To achieve best results, the definition of a new calibration method for structured light systems was established . Based on a large state of the art and also with a proposed classification of these methods, it has been proposed to calibrate a camera projector pair using visual servoing . The validity and the results of this method were tested on the basis of numerous experimental tests conducted under the SRDViand project. Following the development of this method, a prototype bovine cutting was performed .

Fringe-pattern projection (FPP) techniques are commonly used for surface-shape measurement in a wide range of applications including object and scene modeling, part inspection, and reverse engineering. Periodic intensity fringe patterns with a specific amplitude are projected by the projector onto an object and a camera captures images of the fringe patterns, which appear distorted by the object surface from the perspective of the camera. The images are then used to compute the height or depth of the object at each pixel. One of the problems with FPP is that camera sensor saturation may occur if there is a large change in ambient lighting or a large range in surface reflectivity when measuring object surfaces. Camera sensor saturation occurs when the reflected intensity exceeds the maximum quantization level of the camera. A low SNR occurs when there is a low intensity modulation of the fringe pattern compared to the amount of noise in the image. Camera sensor saturation and low SNR can result in significant measurement error. Careful selection of the camera aperture or exposure time can reduce the error due to camera sensor saturation or low SNR. However, this is difficult to perform automatically, which may be necessary when measuring objects in uncontrolled environments where the lighting may change and objects have different surface reflectivity. This research presents three methods to avoid camera sensor saturation when measuring surfaces subject to changes in ambient lighting and objects with a large range in reflectivity. All these methods use the same novel approach of lowering the maximum input gray level (MIGL) to the projector for saturation avoidance. This approach avoids saturation by lowering the reflected intensity so that formerly saturated intensities can be captured by the camera. The first method of saturation avoidance seeks a trade-off between robustness to intensity saturation and low SNR. Measurements of a flat white plate at different MIGL resulted in a trade-off MIGL that yielded the highest accuracy for a single adjustment of MIGL that is uniform within and across the projected images. The second method used several sets of images, taken at constant steps of MIGL, and combined the images pixel-by-pixel into a single set of composite images, by selecting the highest unsaturated intensities at each pixel. White plate measurements using this method had comparable accuracy to the first method but required more images to form the composite image. Measurement of a checkerboard showed a higher accuracy than the first method since the second method maintains a higher SNR when the object has a large range of reflectivity. The last method also used composite images where the step size was determined dynamically, based on the estimated percentage of pixels that would become unsaturated at the next step. In measurements of a flat white plate and a checkerboard the dynamic step size was found to add flexibility to the measurement system compared to the constant steps using the second method. Using dynamic steps, the measurement system was able to measure objects with either a low or high range of reflectivity with high accuracy and without manually adjusting the step size. This permits fully automated measurement of unknown objects with variable reflectivity in unstructured environments with changing lighting conditions. The methods can be used for measurement in uncontrolled environments, for specular surfaces, and those with a large range of reflectivity or luminance. This would allow a wider range of measurement applications using FPP techniques.

The utilisation of 3D digitisation and visualisation has grown considerably since 2008 and is becoming an increasingly useful tool for the digital documentation and metric analysis of archaeological artefacts and skeletal remains. It provides public access to rare and fragile specimens of palaeontological and palaeopathological importance whilst reducing the physical impact on these remains. Research in engineering and computer vision provides some insight into the impact of surface properties such as colour, specularity, reflectance and shape on the quality of the recorded 3D image, but within the archaeological and palaeontological disciplines comparable work has not yet been developed. If archaeology and anthropology are to provide long term reliable data from archaeological and palaeontological specimens in a way that doesn’t require repeated re-digitisation, we need to understand the impacts that the taphonomic histories of such samples have on our ability to 3D record them. Understanding the relationship of these taphonomic histories and the surface and optical properties will promote informed choices about the suitability of recording techniques. This thesis considers the taphonomic processes that affect the preservation of bone over archaeological, forensic and palaeontological timescales and the effect this has on the quality of 3D digital models. The digital refit of fragmentary bone samples is considered in relation to the effect of taphonomic alterations to bone. Conclusions regarding the key taphonomic factors and 3D digital model quality are drawn and areas of further work are identified.

La fabrication de pièces manufacturées génère un nombre très important de données de différents types définissant les géométries de fabrication ainsi que la qualité de production. Ce travail de thèse s’inscrit dans le cadre de la réalisation d’un système de vision cognitif dédié à l’évaluation d’objets 3D manufacturés incluant éventuellement des surfaces gauches, en tenant compte des tolérances géométriques et des incertitudes. Ce système permet un contrôle exhaustif de pièces manufacturées et offre la possibilité d’une inspection tridimensionnelle automatique de la pièce. La mise en place d’un système de mesures multi-capteurs (passifs et actifs) a permis d’améliorer significativement la qualité d’évaluation par le biais d’une reconstruction tridimensionnelle enrichie de l’objet à évaluer. En particulier, nous avons employé simultanément un système stéréoscopique de vision et un système à projection de lumière structurée afin de reconstruire les contours et les surfaces de différents objets 3D. / Producing industrially manufactured parts generates a very large number of data of various types defining the manufacturing geometries as well as the quality of production. This PhD work has been carried out within the framework of the realization of a cognitive vision system dedicated to the 3D evaluation of manufactured objects including possibly free form surfaces, taking into account the geometric tolerances and uncertainties. This system allows the comprehensive control of manufactured parts, and provides the means for their automated 3D dimensional inspection. The implementation of a multi-sensor (passive and active) measuring system enabled to improve significantly the assessment quality through an enriched three-dimensional reconstruction of the object to be evaluated. Specifically, we made use simultaneously of a stereoscopic vision system and of a structured light based system in order to reconstruct the edges and surfaces of various 3D objects.

The utilisation of 3D digitisation and visualisation has grown considerably since 2008 and is becoming an increasingly useful tool for the digital documentation and metric analysis of archaeological artefacts and skeletal remains. It provides public access to rare and fragile specimens of palaeontological and palaeopathological importance whilst reducing the physical impact on these remains. Research in engineering and computer vision provides some insight into the impact of surface properties such as colour, specularity, reflectance and shape on the quality of the recorded 3D image, but within the archaeological and palaeontological disciplines comparable work has not yet been developed. If archaeology and anthropology are to provide long term reliable data from archaeological and palaeontological specimens in a way that doesn’t require repeated re-digitisation, we need to understand the impacts that the taphonomic histories of such samples have on our ability to 3D record them. Understanding the relationship of these taphonomic histories and the surface and optical properties will promote informed choices about the suitability of recording techniques. This thesis considers the taphonomic processes that affect the preservation of bone over archaeological, forensic and palaeontological timescales and the effect this has on the quality of 3D digital models. The digital refit of fragmentary bone samples is considered in relation to the effect of taphonomic alterations to bone. Conclusions regarding the key taphonomic factors and 3D digital model quality are drawn and areas of further work are identified. / Arts and Humanities Research Council

[pt] As pinças ópticas tornaram-se uma ferramenta importante na pesquisa multidisciplinar, permitindo a manipulação e estudo de partículas em micro e nanoescala. Aqui, descrevemos o desenvolvimento de dois experimentos de pinça óptica no cerne da optomecânica levitada: uma pinça óptica a vácuo Gaussiana e uma pinça óptica a vácuo com luz estruturada. No experimento Gaussiano, descrevemos em detalhes sua construção e seu uso para testar características de movimento estocástico sujeito a forças efetivas não-lineares geradas através de feedback elétrico. Em seguida, passamos para a configuração de luz estruturada. Utilizando um Modulador Espacial de Luz, desenvolvemos uma pinça óptica a vácuo com a capacidade de gerar potenciais ópticos arbitrários, incluindo não-linearidades e armadilhas para múltiplas partículas. Os experimentos desenvolvidos neste trabalho abrem caminho para novos métodos de controle de movimento de partículas, forças e interações, expandindo ainda mais a caixa de ferramentas da optomecânica levitada. / [en] Optical tweezers have become an important tool in multidisciplinary research, allowing for the manipulation and study of micro- and nano-scale particles. Here, we describe the development of two optical tweezer experiments at the heart of levitated optomechanics: a Gaussian and a structured light vacuum optical tweezer. In the Gaussian experiment, we describe in detail its construction and its use to test features of stochastic motion subject to nonlinear effective forces generated via electric feedback. Next, we move to the structured light setup. Using a Spatial Light Modulator, we develop a vacuum optical tweezer with the capability of engineering arbitrary optical landscapes, including non-linearities and multi-particle traps. The experiments developed in this work pave the way to novel methods for controlling particle motion, forces and interactions, further extending the levitated optomechanics toolbox.

<p dir="ltr">Monitoring of additive manufacturing (AM) processes allows for saving time and materials by detecting and addressing errors as they occur. When fast and efficient, the monitored AM of each unit can be completed in less time, thus improving overall economics and allowing the user to accept a higher capacity of AM requests with the same number of machines. Based on existing AM process monitoring solutions, it is very challenging for any approach to analyze full-resolution sensor data that yields three-dimensional (3D) topological information for closed-loop real-time applications. It is also challenging for any approach to be simultaneously capable of <i>plug-and-play</i> operation once AM hardware and sensor subsystems are configured. This thesis presents a novel method to speed up error detection in an additive manufacturing (AM) process by minimizing the necessary three-dimensional (3D) reconstruction and comparison. A structured light 3D imaging technique is developed that has native pixel-by-pixel mapping between the captured two-dimensional (2D) absolute phase image and the reconstructed 3D point cloud. This 3D imaging technique allows error detection to be performed in the 2D absolute phase image domain prior to 3D point cloud generation, which drastically reduces complexity and computational time. For each layer of an AM process, an artificial threshold phase image is generated and compared to the measured absolute phase image to identify error regions. Compared to an existing AM error detection method based on 3D reconstruction and point cloud processing, experimental results from a material extrusion (MEX) AM process demonstrate that the proposed method has comparable error detection capabilities. The proposed method also significantly increases the error detection speed, where the relationship between the speed improvement factor and the percentage of erroneous pixels in the captured 2D image follows a power-law relationship. The proposed method was also successfully used to implement closed-loop error correction to demonstrate a potential process monitoring application.</p>

<p dir="ltr">Over the last few decades, three-dimensional (3D) optical imaging and sensing techniques have attracted much attention from both academia and industries. Owing to its capability of gathering more information than conventional 2D imaging, it has been successfully adopted in many applications on the macro scale which ranges from sub-meters to meters such as entertainment, commercial electronics, manufacturing, and construction. For example, the iPhone “FaceID” sensor is used for facial recognition, and the Microsoft Kinect is used to track body motion in video games. With recent advances in many technical fields, such as semiconductor packaging, additive manufacturing, and micro-robots, there is an increasing need for microscopic 3D imaging, and several techniques including interferometry, confocal microscopy, focus variation, and structured light have been developed and adopted in these industries. Among these techniques, the structured light 3D imaging technique is considered one of the most promising techniques for in-situ metrology, owing to its advantage of simple configuration and high measurement speed. However, several challenges must be addressed in employing the structured-light 3D imaging technique in these fields.</p><p dir="ltr">The first challenge is the limited measurement range caused by the limited depth of field (DOF). Given the necessity for large magnification in the microscopic structured light system, the DOF becomes notably shallow, especially when pin-hole lenses are adopted. This issue is exacerbated by the fact that the measured objects in the aforementioned industries could contain miniaturized features spanning a broad height range. To address this problem, we introduce the idea of the focus stacking technique, wherein the focused pixels gathered from various focus settings are merged to form an all-in-focus image, into the structured-light 3D imaging. We further developed a computational framework that utilizes the phase information and fringe contrast of the projected fringe patterns to mitigate the influence of object textures.</p><p dir="ltr">The second challenge is the 3D imaging speed. The 3D measurement speed is a crucial factor for in-situ applications. We improved the large DOF 3D imaging speed by reducing the required fringe images from two aspects: 1) We developed a calibration method for multifocus pin-hole mode, which can eliminate the necessity of the 2D image alignment. The conventional method based on circle patterns will be affected during the feature extraction process by the significant camera defocusing. In contrast, our proposed method is more robust since it uses virtual features extracted from a reconstructed white flat surface under a pre-calibrated focus setting. 2)We developed a phase unwrapping method with the assistance of the electrically tunable lens (ETL), which is an optical component we used to capture fringe images under various focus settings. The proposed phase unwrapping method leverages the focal plane position of each focus setting to estimate a rough depth map for the geometric-constraint phase unwrapping algorithm. By doing this, the method eliminates the limitation on the effective working depth range and becomes feasible in large DOF 3D imaging.</p><h4>Even with all previous methodologies, the efficiency of large DOF 3D imaging is still not high enough under certain circumstances. One of the major reasons is that we can still only use a series of pre-defined focus settings to run the focus stacking, since we have no prior on the measured objects. This issue could lead to low measurement efficiency when the depth range of the measured objects does not cover the whole enlarged DOF. To improve the performance of the system under such situations, we developed a method that introduces another computational imaging technique: the focal sweep technique, to help determine the optimal focus settings adapting to different measured objects.</h4><h4>In summary, this dissertation contributed to high-speed, large depth-of-field, and automated 3D imaging, which can be used in micro-scale applications from the following aspects: (1) enlarging the DOF of the microscopic 3D imaging using the focus stacking technique; (2) developing methods to improve the speed of large DOF microscopic 3D imaging; and (3) developing a method to improve the efficiency of the focus stacking under certain circumstances. These contributions can potentially enable the structured-light 3D imaging technique to be an alternative 3D microscopy approach for many academic studies and industry applications.</h4><p></p>