985 resultados para force sensor calibration
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National Highway Traffic Safety Administration, Washington, D.C.
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National Highway Traffic Safety Administration, Washington, D.C.
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"May 1974."
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"May 1974."
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"May 1997."
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Photocopy.
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The research developed in this thesis explores the sensing and inference of human movement in a dynamic way, as opposed to conventional measurement systems, that are only concerned with discrete evaluations of stimuli in sequential time. Typically, conventional approaches are used to infer the dynamic movement of the body; such as vision and motion tracking devices, with either a human diagnosis or complex image processing algorithm to classify the movement. This research is therefore the first of its kind to attempt and provide a movement classifying algorithm through the use of minimal sensing points, with the application for this novel system, to classify human movement during a golf swing. There are two main categories of force sensing. Firstly, array-type systems consisting of many sensing elements, and are the most commonly researched and commercially available. Secondly, reduced force sensing element systems (RFSES) also known as distributive systems have only been recently exploited in the academic world. The fundamental difference between these systems is that array systems handle the data captured from each sensor as unique outputs and suffer the effects of resolution. The effect of resolution, is the error in the load position measurement between sensing elements, as the output is quantized in terms of position. This can be compared to a reduced sensor element system that maximises that data received through the coupling of data from a distribution of sensing points to describe the output in discrete time. Also this can be extended to a coupling of transients in the time domain to describe an activity or dynamic movement. It is the RFSES that is to be examined and exploited in the commercial sector due to its advantages over array-based approaches such as reduced design, computational complexity and cost.
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The diagnosis of ocular disease is increasingly important in optometric practice and there is a need for cost effective point of care assays to assist in that. Although tears are a potentially valuable source of diagnostic information difficulties associated with sample collection and limited sample size together with sample storage and transport have proved major limitations. Progressive developments in electronics and fibre optics together with innovation in sensing technology mean that the construction of inexpensive point of care fibre optic sensing devices is now possible. Tear electrolytes are an obvious family of target analytes, not least to complement the availability of devices that make the routine measurement of tear osmolarity possible in the clinic. In this paper we describe the design, fabrication and calibration of a fibre-optic based electrolyte sensor for the quantification of potassium in tears using the ex vivo contact lens as the sample source. The technology is generic and the same principles can be used in the development of calcium and magnesium sensors. An important objective of this sensor technology development is to provide information at the point of routine optometric examination, which would provide supportive evidence of tear abnormality.
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Combined the large evanescent field of microfiber with the high thermal conductivity of graphene, a sensitive all-fiber temperature sensor based on graphene-assisted micro fiber is proposed and experimentally demonstrated. Microfiber can be easily attached with graphene due to the electrostatic 6 force, resulting in an effective interaction between graphene and the evanescent field of microfiber. The change of the ambient temperature has a great influence on the conductivity of graphene, leading to the variation of the effective refractive index of microfiber. Consequently, the optical power transmission will be changed. The temperature sensitivity of 0.1018 dB/°C in the heating process and 0.1052 dB/°C in the cooling process as well as a high resolution of 0.0098 °C is obtained in the experiment. The scheme may have great potential in sensing fields owing to the advantages of high sensitivity, compact size, and low cost.
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The stress sensitivity of polymer optical fibre (POF) based Fabry-Perot sensors formed by two uniform Bragg gratings with finite dimensions is investigated. POF has received high interest in recent years due to its different material properties compared to its silica counterpart. Biocompatibility, a higher failure strain and the highly elastic nature of POF are some of the main advantages. The much lower Young’s modulus of polymer materials compared to silica offers enhanced stress sensitivity to POF based sensors which renders them great candidates for acoustic wave receivers and any kind of force detection. The main drawback in POF technology is perhaps the high fibre loss. In a lossless fibre the sensitivity of an interferometer is proportional to its cavity length. However, the presence of the attenuation along the optical path can significantly reduce the finesse of the Fabry-Perot interferometer and it can negatively affect its sensitivity at some point. The reflectivity of the two gratings used to form the interferometer can be also reduced as the fibre loss increases. In this work, a numerical model is developed to study the performance of POF based Fabry-Perot sensors formed by two uniform Bragg gratings with finite dimensions. Various optical and physical properties are considered such as grating physical length, grating effective length which indicates the point where the light is effectively reflected, refractive index modulation of the grating, cavity length of the interferometer, attenuation and operating wavelength. Using this model, we are able to identify the regimes in which the PMMA based sensor offer enhanced stress sensitivity compared to silica based one.
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Bio-molecular interactions exist ubiquitously in all biological systems. This dissertation project was to construct a powerful surface plasmon resonance (SPR) sensor. The SPR system is used to study bio-molecular interactions in real time and without labeling. Surface plasmon is the oscillation of free electrons in metals coupled with surface electromagnetic waves. These surface electromagnetic waves provide a sensitive probe to study bio-molecular interactions on metal surfaces. This project resulted in the successful construction and optimization of a homemade SPR sensor and the development of several new powerful protocols to study bio-molecular interactions. It was discovered through this project that the limitations of earlier SPR sensors are related not only to the instrumentation design and operating procedures, but also to the complex behaviors of bio-molecules on sensor surfaces that were very different from that in solution. Based on these discoveries the instrumentation design and operating procedures were fully optimized. A set of existing sensor surface treatment protocols were tested and evaluated and new protocols were developed in this project. The new protocols have demonstrated excellent performance to study biomolecular interactions. The optimized home-made SPR sensor was used to study protein-surface interactions. These protein-surface interactions are responsible for many complex organic cell activities. The co-existence of different driving forces and their correlation with the structure of the protein and the surface make the understanding of the fundamental mechanism of protein-surface interactions a very challenging task. Using the improved SPR sensor, the electrostatic interaction and hydrophobic interaction were studied separately. The results of this project directly confirmed the theoretical predictions for electrostatic force between the protein and surface. In addition, this project demonstrated that the strength of the protein-surface hydrophobic interaction does not solely depend on the hydrophobicity as reported earlier. Surface structure also plays a significant role.
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Dynamic processes such as morphogenesis and tissue patterning require the precise control of many cellular processes, especially cell migration. Historically, these processes are thought to be mediated by genetic and biochemical signaling pathways. However, recent advances have unraveled a previously unappreciated role of mechanical forces in regulating these homeostatic processes in of multicellular systems. In multicellular systems cells adhere to both deformable extracellular matrix (ECM) and other cells, which are sources of applied forces and means of mechanical support. Cells detect and respond to these mechanical signals through a poorly understood process called mechanotransduction, which can have profound effects on processes such as cell migration. These effects are largely mediated by the sub cellular structures that link cells to the ECM, called focal adhesions (FAs), or cells to other cells, termed adherens junctions (AJs).
Overall this thesis is comprised of my work on identifying a novel force dependent function of vinculin, a protein which resides in both FAs and AJs - in dynamic process of collective migration. Using a collective migration assay as a model for collective cell behavior and a fluorescence resonance energy transfer (FRET) based molecular tension sensor for vinculin I demonstrated a spatial gradient of tension across vinculin in the direction of migration. To define this novel force-dependent role of vinculin in collective migration I took advantage of previously established shRNA based vinculin knock down Marin-Darby Canine Kidney (MDCK) epithelial cells.
The first part of my thesis comprises of my work demonstrating the mechanosensitive role of vinculin at AJ’s in collectively migrating cells. Using vinculin knockdown cells and vinculin mutants, which specifically disrupt vinculin’s ability to bind actin (VinI997A) or disrupt its ability to localize to AJs without affecting its localization at FAs (VinY822F), I establish a role of force across vinculin in E-cadherin internalization and clipping. Furthermore by measuring E-cadherin dynamics using fluorescence recovery after bleaching (FRAP) analysis I show that vinculin inhibition affects the turnover of E-cadherin at AJs. Together these data reveal a novel mechanosensitive role of vinculin in E-cadherin internalization and turnover in a migrating cell layer, which is contrary to the previously identified role of vinculin in potentiating E-cadherin junctions in a static monolayer.
For the last part of my thesis I designed a novel tension sensor to probe tension across N-cadherin (NTS). N-cadherin plays a critical role in cardiomyocytes, vascular smooth muscle cells, neurons and neural crest cells. Similar to E-cadherin, N-cadherin is also believed to bear tension and play a role in mechanotransduction pathways. To identify the role of tension across N-cadherin I designed a novel FRET-based molecular tension sensor for N-cadherin. I tested the ability of NTS to sense molecular tension in vascular smooth muscle cells, cardiomyocytes and cancer cells. Finally in collaboration with the Horwitz lab we have been able to show a role of tension across N-cadherin in synaptogenesis of neurons.
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With the main focus on safety, design of structures for vibration serviceability is often overlooked or mismanaged, resulting in some high profile structures failing publicly to perform adequately under human dynamic loading due to walking, running or jumping. A standard tool to inform better design, prove fitness for purpose before entering service and design retrofits is modal testing, a procedure that typically involves acceleration measurements using an array of wired sensors and force generation using a mechanical shaker. A critical but often overlooked aspect is using input (force) to output (response) relationships to enable estimation of modal mass, which is a key parameter directly controlling vibration levels in service.
This paper describes the use of wireless inertial measurement units (IMUs), designed for biomechanics motion capture applications, for the modal testing of a 109 m footbridge. IMUs were first used for an output-only vibration survey to identify mode frequencies, shapes and damping ratios, then for simultaneous measurement of body accelerations of a human subject jumping to excite specific vibrations modes and build up bridge deck accelerations at the jumping location. Using the mode shapes and the vertical acceleration data from a suitable body landmark scaled by body mass, thus providing jumping force data, it was possible to create frequency response functions and estimate modal masses.
The modal mass estimates for this bridge were checked against estimates obtained using an instrumented hammer and known mass distributions, showing consistency among the experimental estimates. Finally, the method was used in an applied research application on a short span footbridge where the benefits of logistical and operational simplicity afforded by the highly portable and easy to use IMUs proved extremely useful for an efficient evaluation of vibration serviceability, including estimation of modal masses.
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In acoustic instruments, the controller and the sound producing system often are one and the same object. If virtualacoustic instruments are to be designed to not only simulate the vibrational behaviour of a real-world counterpart but also to inherit much of its interface dynamics, it would make sense that the physical form of the controller is similar to that of the emulated instrument. The specific physical model configuration discussed here reconnects a (silent) string controller with a modal synthesis string resonator across the real and virtual domains by direct routing of excitation signals and model parameters. The excitation signals are estimated in their original force-like form via careful calibration of the sensor, making use of adaptive filtering techniques to design an appropriate inverse filter. In addition, the excitation position is estimated from sensors mounted under the legs of the bridges on either end of the prototype string controller. The proposed methodology is explained and exemplified with preliminary results obtained with a number of off-line experiments.
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Many-core systems are emerging from the need of more computational power and power efficiency. However there are many issues which still revolve around the many-core systems. These systems need specialized software before they can be fully utilized and the hardware itself may differ from the conventional computational systems. To gain efficiency from many-core system, programs need to be parallelized. In many-core systems the cores are small and less powerful than cores used in traditional computing, so running a conventional program is not an efficient option. Also in Network-on-Chip based processors the network might get congested and the cores might work at different speeds. In this thesis is, a dynamic load balancing method is proposed and tested on Intel 48-core Single-Chip Cloud Computer by parallelizing a fault simulator. The maximum speedup is difficult to obtain due to severe bottlenecks in the system. In order to exploit all the available parallelism of the Single-Chip Cloud Computer, a runtime approach capable of dynamically balancing the load during the fault simulation process is used. The proposed dynamic fault simulation approach on the Single-Chip Cloud Computer shows up to 45X speedup compared to a serial fault simulation approach. Many-core systems can draw enormous amounts of power, and if this power is not controlled properly, the system might get damaged. One way to manage power is to set power budget for the system. But if this power is drawn by just few cores of the many, these few cores get extremely hot and might get damaged. Due to increase in power density multiple thermal sensors are deployed on the chip area to provide realtime temperature feedback for thermal management techniques. Thermal sensor accuracy is extremely prone to intra-die process variation and aging phenomena. These factors lead to a situation where thermal sensor values drift from the nominal values. This necessitates efficient calibration techniques to be applied before the sensor values are used. In addition, in modern many-core systems cores have support for dynamic voltage and frequency scaling. Thermal sensors located on cores are sensitive to the core's current voltage level, meaning that dedicated calibration is needed for each voltage level. In this thesis a general-purpose software-based auto-calibration approach is also proposed for thermal sensors to calibrate thermal sensors on different range of voltages.