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Nonwoven materials are engineered fabrics, produced by bonding constituent fibres together by mechanical, thermal or chemical means. Such a technology has a great potential to produce material for specific purposes. It is therefore crucial to develop right products with requested properties. This requires a good understanding of the macro and micro behaviours of nonwoven products. In last 40 years, many efforts have been made by researchers to understand the performance of nonwoven materials. One of the main research challenges on the way to this understanding is to link the properties of fibres and the fabric's random fibrous microstructure to the mechanisms of overall material's deformation. The purpose of this research is to study experimentally and numerically the deformation mechanisms of a low-density thermally bonded nonwoven fabric (fibre: Polypropylene; density: 20 gsm). The study started with tensile experiments for the nonwoven material. Specimens with varying dimensions and shapes were tested to investigate the size-dependent deformation mechanisms of the material. Based on obtained results, representative dimensions for the material are determined and used in other experimental and numerical studies. Then standard tensile tests were performed coupled with image analysis. Analysis of the obtained results, allowed the tensile behaviour of the nonwoven material to be determined, the initial study of the effects of material's nonuniform microstructure was also implemented. Based on the experimental results obtained from tensile tests, continuous finite-element models were developed to simulate the material properties of the nonwoven material for its two principle directions: machine direction (MD) and cross direction (CD). Due to the continuous nature of the models, they were only used to establish the mechanical behaviour of the material by treating it as a two-component composite. The effects of bond points, which are a stiffer component within the material, were analysed. Due to the limitations of the continuous FE models, experimental studies were performed focused on the material s microstructure. The latter was detected using an x-ray Micro CT system and an ARAMIS optical strain analysis system. According to the obtained images, the nonwoven fabric is a three-component material. The effects of material's microstructure on stress/strain distributions in the deformed material were studied using advanced image analysis techniques. Based on the experimental results, a new stress calculation method was suggested to substitute the traditional approach, which is not suitable for the analysis of the low density nonwoven material. Then, the fibres orientation distribution and material properties of single fibres were measured due to their significant effects on overall mechanical properties. Finally, discontinuous finite-element models were developed accounting for on the material's three-component structure. The models emphasised the effects of the nonuniform and discontinuous microstructure of the material. Mechanical properties of fibres, the density of fibrous network, the fibres orientation distribution and the arrangement of bond points were used as input parameters for the models, representing features of the material's microstructure. With the use of the developed discontinuous models, the effects of material's microstructure on deformation mechanisms of the low-density nonwoven material were analysed.

This thesis reports the development of high performance readout electronics for resistive microbolometer detector arrays that are used for uncooled infrared imaging. Three different readout chips are designed and fabricated by using a standard 0.6 &micro / m CMOS process. Fabricated chips include a conventional capacitive transimpedance amplifier (CTIA) type readout circuit, a novel readout circuit with dynamic resistance nonuniformity compensation capability, and a new improved version of the CTIA circuit. The fabricated CTIA type readout circuit uses two digital-to-analog converters (DACs) with multiple analog buses which compensate the resistance nonuniformity by adjusting the bias currents of detector and reference resistors. Compensated detector current is integrated by a switched capacitor integrator with offset cancellation capability followed by a sample-and-hold circuit. The measured detector referred current noise is 47.2 pA in an electrical bandwidth of 2.6 KHz, corresponding to an expected SNR of 530. The dynamic nonuniformity compensation circuit uses a feedback structure that dynamically changes the bias currents of the reference and detector resistors. A special feature of the circuit is that it provides continuous compensation for the detector and reference resistances due to temperature changes over time. Test results of the fabricated circuit show that the circuit reduces the offset current due to resistance nonuniformity 42.5 times. However, the calculated detector referred current noise is 360 pA, which limits the circuit SNR to 70. The improved CTIA type readout circuit introduces a new detector biasing method by using an additional auxiliary biasing transistor for better current controllability. The improved readout circuit alleviates the need for high resolution compensation DACs, which drastically decreases the circuit area. The circuit occupies an area of one seventh of the first design. According to test results, the current compensation ratio is 170, and the detector referred current noise is 48.6 pA in a 2.6 KHz bandwidth.

In this work a machine vision system for inspecting pharmaceutical color tablets is presented and implemented. Nonparametric clustering based segmentation is faster and thus more appropriate for real-time applications. Two nonparametric clustering based methods, Nearest Neighbor algorithm and MaxShift algorithm are worked in RGB and HSV color spaces as the segmentation step. The implemented algorithm allows the system to detect the missing and broken tablets, tablet fragments, and the color, size, and shape of individual tablets in pharmaceutical blisters, in real-time. System has two operation modes called &amp / #8216 / &amp / #8216 / training&amp / #8217 / &amp / #8217 / and &amp / #8216 / &amp / #8216 / inspection&amp / #8217 / &amp / #8217 / mode, respectively. Operator selects one point on any tablet in a defect-free training captured image in the &amp / #8216 / &amp / #8216 / training&amp / #8217 / &amp / #8217 / mode. In the correction step an optimization algorithm is required, for which Powell and Downhill Simplex methods are used. Captured image is then corrected for spatial color nonuniformity, segmented, and the position, size, shape, and color of each tablet are extracted in the training mode. The correction and segmentation models / the extracted features generated in the training mode is saved with the user defined values to form the model. Each acquired image in the inspection mode is corrected and segmented according to the blister model and then the blisters are classified as &amp / #8216 / &amp / #8216 / good&amp / #8217 / &amp / #8217 / or &amp / #8216 / &amp / #8216 / bad&amp / #8217 / &amp / #8217 / by comparing the extracted feature values with the user defined tolerances stored in the blister model.

<p>This thesis describes and evaluates a number of algorithms for reducing fixed pattern noise in image sequences. Fixed pattern noise is the dominantnoise component for many infrared detector systems, perceived as a superimposed pattern that is approximately constant for all image frames. </p><p>Primarily, methods based on estimation of the movement between individual image frames are studied. Using scene-matching techniques, global motion between frames can be successfully registered with sub-pixel accuracy. This allows each scene pixel to be traced along a path of individual detector elements. Assuming a static scene, differences in pixel intensities are caused by fixed pattern noise that can be estimated and removed. </p><p>The algorithms have been tested by using real image data from existing infrared imaging systems with good results. The tests include both a two-dimensional focal plane array detector and a linear scanning one-dimensional detector, in different scene conditions.</p>

This thesis describes and evaluates a number of algorithms for reducing fixed pattern noise in image sequences. Fixed pattern noise is the dominantnoise component for many infrared detector systems, perceived as a superimposed pattern that is approximately constant for all image frames. Primarily, methods based on estimation of the movement between individual image frames are studied. Using scene-matching techniques, global motion between frames can be successfully registered with sub-pixel accuracy. This allows each scene pixel to be traced along a path of individual detector elements. Assuming a static scene, differences in pixel intensities are caused by fixed pattern noise that can be estimated and removed. The algorithms have been tested by using real image data from existing infrared imaging systems with good results. The tests include both a two-dimensional focal plane array detector and a linear scanning one-dimensional detector, in different scene conditions.

This thesis describes the development of a sensing technique for temperature nonuniformity along the line of sight through combustion exhaust, geared for gas turbine applications. Tunable diode laser absorption spectroscopy is used to measure three absorption lines and compute a variable to characterize the level of temperature nonuniformity along the laser path. Nonuniformity information is obtained from one line of sight sensor because the absorption has a nonlinear dependence on temperature. This dependence is analyzed to determine the behaviour, shape, and response of absorption lines measured through mediums with nonuniform temperature profiles. Based on this analysis a new line selection process for nonuniformity sensing is developed. A sensor for temperature nonuniformity is proposed and demonstrated through computer simulations and experiments in the exhaust of a laboratory-scale combustor. The nonuniformity variable, U, is shown to monotonically track the level of temperature nonuniformity along the laser path. The capabilities of this sensing technique are determined based on a comprehensive analysis of errors and their effect on sensor performance. Methods to mitigate these errors are described, and the overall sensor capability is determined based on the characteristics of state of the art diode laser and absorption sensor technology. Such a sensor is capable of measuring minimum temperature deviations of 17% or more, which is well within the needed capabilities for industrial applications. Furthermore, the results and knowledge presented in this thesis apply to other absorption based sensing techniques.

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A procedure was developed for dealing with two problems that have impeded the use of quantal parameters in studies of transmitter release. The first, involving temporal and spatial biasing in the estimates for the number of functional release sites (n̄) and probability of release (p̄), was addressed by reducing temporal variance experimentally and calculating the bias produced by spatial variance in p (var(s)p). The second, involving inaccuracies in the use of nerve-evoked endplate potentials (EPPs), was circumvented by using only miniature EPPs (MEPPs). Intracellular recordings were made from isolated frog cutaneous pectoris, after decapitation and pithing of the animals, and the concentration of K+ ([K+]) was raised to 10 mM to increase the level of transmitter release. The number of quanta released (m̄) by the EPP was replaced by the number of MEPPs in a fixed time interval (bin), and 500 sequential bins used for each quantal estimate. With the use of 50-ms bins, estimates for var(s)p were consistently negative. This was due to too large a bin (and introduction of undetected temporal variance) because the use of smaller bins (5 ms) produced positive estimates of var(s)p. Increases in m, n, and p but not var(s)p were found in response to increases in [K+] or [Ca2+]/[Co2+]. La3+ (20 μM) produced increases in m and n, which peaked after 20 min and declined toward zero. There were also large increases in p and var(s)p, which peaked and declined only to initial control values. The increase in var(s)p was presumed to reflect La3+-induced release of Ca2+ from intracellular organelles. The results suggest that this approach may be used to obtain unbiased estimates of n̄ and p̄ and that the estimates of var(s)p may be useful for studying Ca2+ release from intraterminal organelles.

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