Dissertations / Theses on the topic 'Sensor modelling'
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Gerra, Guido. "Electromagnetic modelling of superconducting sensor designs." Thesis, University of Cambridge, 2003. https://www.repository.cam.ac.uk/handle/1810/104788.
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The problem of design optimisation of thin film direct current Superconducting QUantum Interference Device (SQUID) magnetometers made of YBCO (YBa2Cu3O7-x) was considered. The inductances and effective areas were calculated using the software package 3D-MLSI. Resolution and reliability issues were first tested on simple superconducting systems, showing good agreement with analytical formulae and experimental results, and demonstrating that a remarkable precision can be obtained though at the expense of CPU time and memory. The software was then used to simulate a SQUID magnetometer fabricated in the Device Materials Group of the Department of Materials Science and Metallurgy, proving that 3D-MLSI can be used to predict the parameters of real systems with acceptable accuracy.
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Lin, Min. "Channel modelling for wireless sensor networks." Thesis, University of Cambridge, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611656.
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Singh, Hanumant. "An entropic framework for AUV sensor modelling." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11449.
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Lim, Shen Hin Mechanical & Manufacturing Engineering Faculty of Engineering UNSW. "Calibration-free image sensor modelling: deterministic and stochastic." Awarded by:University of New South Wales. Mechanical & Manufacturing Engineering, 2009. http://handle.unsw.edu.au/1959.4/44563.
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This dissertation presents the calibration-free image sensor modelling process applicable for localisation, such that these are robust to changes in environment and in sensor properties. The modelling process consists of two distinct parts, which are deterministic and stochastic techniques, and is achieved using mechanistic deconvolution, where the sensor???s mechanical and electrical properties are utilised. In the deterministic technique, the sensor???s effective focal length is first estimated by known lens properties, and is used to approximate the lens system by a thick lens and its properties. The aperture stop position offset???which is one of the thick lens properties???then derives a new factor, namely calibration-free distortion effects factor, to characterise distortion effects inherent in the sensor. Using this factor and the given pan and tilt angles of an arbitrary plane of view, the corrected image data is generated. The corrected data complies with the image sensor constraints modified by the pan and tilt angles. In the stochastic technique, the stochastic focal length and distortion effects factor are first approximated, using tolerances of the mechanical and electrical properties. These are then utilised to develop the observation likelihood necessary in recursive Bayesian estimation. The proposed modelling process reduces dependency on image data, and, as a result, do not require experimental setup or calibration. An experimental setup was constructed to conduct extensive analysis on accuracy of the proposed modelling process and its robustness to changes in sensor properties and in pan and tilt angles without recalibration. This was compared with a conventional modelling process using three sensors with different specifications and achieved similar accuracy with one-seventh the number of iterations. The developed model has also shown itself to be robust and, in comparison to the conventional modelling process, reduced the errors by a factor of five. Using area coverage method and one-step lookahead as control strategies, the stochastic sensor model was applied into a recursive Bayesian estimation application and was also compared with a conventional approach. The proposed model provided better target estimation state, and also achieved higher efficiency and reliability when compared with the conventional approach.
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Konstatinos, Sasloglou. "Channel measurements and modelling for sensor network applications." Thesis, University of Strathclyde, 2010. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=12833.
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Bach, Thomas William. "Design, modelling and applications of capacitive sensor arrays." Thesis, University of Sussex, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.436252.
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Crowcombe, James Edward. "Larval zebrafish electrocardiography electrodynmaic modelling and sensor design." Thesis, University of Birmingham, 2017. http://etheses.bham.ac.uk//id/eprint/7545/.
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This thesis presents the first model of the electrical activity of the larval zebrafish heart as well as the design and fabrication of novel electrode arrays that were created to measure the electrocardiogram. The model consists of realistic 3D geometry of a 3 day’s post fertilisation zebrafish heart and body with a bidomain electrical model that uses the Fitzhugh-Nagumo equations as the ionic model. The model is able to replicate experimentally observed conduction velocities and action potentials by using region specific parameters and simulate electrocardiograms that are comparable to measurements. The electrode arrays are constructed from flexible polyimide films with gold microelectrodes. These devices have the potential to improve the measurement of the electrocardiogram for drug screening applications as an alternative to the use of micropipette electrodes. Gold plating and PEDOT:PSS coating techniques were applied to the devices to successfully reduce electrode impedance with the effectiveness of each technique categorised using impedance spectroscopy. The devices were tested in vivo with larval zebrafish with limited success and so in vitro tests were conducted using an artificial current source.
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Adero, Frederick. "Modelling and performability evaluation of Wireless Sensor Networks." Thesis, Middlesex University, 2016. http://eprints.mdx.ac.uk/21217/.
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This thesis presents generic analytical models of homogeneous clustered Wireless Sensor Networks (WSNs) with a centrally located Cluster Head (CH) coordinating cluster communication with the sink directly or through other intermediate nodes. The focus is to integrate performance and availability studies of WSNs in the presence of sensor nodes and channel failures and repair/replacement. The main purpose is to enhance improvement of WSN Quality of Service (QoS). Other research works also considered in this thesis include modelling of packet arrival distribution at the CH and intermediate nodes, and modelling of energy consumption at the sensor nodes. An investigation and critical analysis of wireless sensor network architectures, energy conservation techniques and QoS requirements are performed in order to improve performance and availability of the network. Existing techniques used for performance evaluation of single and multi-server systems with several operative states are investigated and analysed in details. To begin with, existing approaches for independent (pure) performance modelling are critically analysed with highlights on merits and drawbacks. Similarly, pure availability modelling approaches are also analysed. Considering that pure performance models tend to be too optimistic and pure availability models are too conservative, performability, which is the integration of performance and availability studies is used for the evaluation of the WSN models developed in this study. Two-dimensional Markov state space representations of the systems are used for performability modelling. Following critical analysis of the existing solution techniques, spectral expansion method and system of simultaneous linear equations are developed and used to solving the proposed models. To validate the results obtained with the two techniques, a discrete event simulation tool is explored. In this research, open queuing networks are used to model the behaviour of the CH when subjected to streams of traffic from cluster nodes in addition to dynamics of operating in the various states. The research begins with a model of a CH with an infinite queue capacity subject to failures and repair/replacement. The model is developed progressively to consider bounded queue capacity systems, channel failures and sleep scheduling mechanisms for performability evaluation of WSNs. Using the developed models, various performance measures of the considered system including mean queue length, throughput, response time and blocking probability are evaluated. Finally, energy models considering mean power consumption in each of the possible operative states is developed. The resulting models are in turn employed for the evaluation of energy saving for the proposed case study model. Numerical solutions and discussions are presented for all the queuing models developed. Simulation is also performed in order to validate the accuracy of the results obtained. In order to address issues of performance and availability of WSNs, current research present independent performance and availability studies. The concerns resulting from such studies have therefore remained unresolved over the years hence persistence poor system performance. The novelty of this research is a proposed integrated performance and availability modelling approach for WSNs meant to address challenges of independent studies. In addition, a novel methodology for modelling and evaluation of power consumption is also offered. Proposed model results provide remarkable improvement on system performance and availability in addition to providing tools for further optimisation studies. A significant power saving is also observed from the proposed model results. In order to improve QoS for WSN, it is possible to improve the proposed models by incorporating priority queuing in a mixed traffic environment. A model of multi-server system is also appropriate for addressing traffic routing. It is also possible to extend the proposed energy model to consider other sleep scheduling mechanisms other than On-demand proposed herein. Analysis and classification of possible arrival distribution of WSN packets for various application environments would be a great idea for enabling robust scientific research.
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Rydén, Alex, and Mattias Langsér. "Data-driven Strain Sensor Modelling in Mining Applications : Artificial strain sensors for material fatigue estimation." Thesis, Linköpings universitet, Fordonssystem, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176682.
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When boring machines are used, large loads are exerted on their structure. The load cycles cause material fatigue on the boring machine structure. If the material fatigue can be estimated in real-time, maintenance can be planned more efficiently and the effect of different types of usage can be evaluated. Because of the many advantages of knowing the material fatigue, the goal of this thesis is to develop a model to predict the strain of a boring machine structure and then derive an estimate of the material fatigue caused by the strain. To do this several approaches using machine learning techniques are evaluated. The input signals were selected using both coherence analysis and mutual information. It was found that linear models outperform the tested non-linear model structures, and that non-linear mechanical connections cause difficulties. The signals to be modelled contained high frequency components that were not present in the available input signals. The results show that given favorable sensor positions, an estimate of the material fatigue can be made with sufficient accuracy when using a noise model and noise realization to cover the non-existent high frequency components.
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Ahmad, Naeem. "Modelling and optimization of sky surveillance visual sensor network." Licentiate thesis, Mittuniversitetet, Institutionen för informationsteknologi och medier, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-17123.
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A Visual Sensor Network (VSN) is a distributed system of a largenumber of camera sensor nodes. The main components of a camera sensornode are image sensor, embedded processor, wireless transceiver and energysupply. The major difference between a VSN and an ordinary sensor networkis that a VSN generates two dimensional data in the form of an image, whichcan be exploited in many useful applications. Some of the potentialapplication examples of VSNs include environment monitoring, surveillance,structural monitoring, traffic monitoring, and industrial automation.However, the VSNs also raise new challenges. They generate large amount ofdata which require higher processing powers, large bandwidth requirementsand more energy resources but the main constraint is that the VSN nodes arelimited in these resources.This research focuses on the development of a VSN model to track thelarge birds such as Golden Eagle in the sky. The model explores a number ofcamera sensors along with optics such as lens of suitable focal length whichensures a minimum required resolution of a bird, flying at the highestaltitude. The combination of a camera sensor and a lens formulate amonitoring node. The camera node model is used to optimize the placementof the nodes for full coverage of a given area above a required lower altitude.The model also presents the solution to minimize the cost (number of sensornodes) to fully cover a given area between the two required extremes, higherand lower altitudes, in terms of camera sensor, lens focal length, camera nodeplacement and actual number of nodes for sky surveillance.The area covered by a VSN can be increased by increasing the highermonitoring altitude and/or decreasing the lower monitoring altitude.However, it also increases the cost of the VSN. The desirable objective is toincrease the covered area but decrease the cost. This objective is achieved byusing optimization techniques to design a heterogeneous VSN. The core ideais to divide a given monitoring range of altitudes into a number of sub-rangesof altitudes. The sub-ranges of monitoring altitudes are covered by individualsub VSNs, the VSN1 covers the lower sub-range of altitudes, the VSN2 coversthe next higher sub-range of altitudes and so on, such that a minimum cost isused to monitor a given area.To verify the concepts, developed to design the VSN model, and theoptimization techniques to decrease the VSN cost, the measurements areperformed with actual cameras and optics. The laptop machines are used withthe camera nodes as data storage and analysis platforms. The area coverage ismeasured at the desired lower altitude limits of homogeneous as well asheterogeneous VSNs and verified for 100% coverage. Similarly, the minimumresolution is measured at the desired higher altitude limits of homogeneous aswell as heterogeneous VSNs to ensure that the models are able to track thebird at these highest altitudes.
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Udoudo, Ofonime. "Modelling the efficiency of an automated sensor-based sorter." Thesis, University of Exeter, 2010. http://hdl.handle.net/10036/118786.
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For future development of automated sensor-based sorting in the mining industry, an improvement in the separation efficiency of the equipment is desirable. This could be achieved through a better understanding of the identification and separation aspects of the automated sorter. For automated sorters that undertake separation through the use of compressed air jets, the problem of poor separation efficiency has been linked with co-deflection losses. Co-deflection losses occur as particles meant to pass on to the ‘accept’ bin are co-deflected with the particles (which are to be deflected) meant to go to the ‘reject’ bin. To study co-deflection losses and suggest means of improving automated sorter separation efficiency, this research investigates the effects of particle size, shape, throughput, together with the proportion of particles (out of the total test batch) required to be deflected on separation efficiency. The effect of the air valve configuration on separation efficiency was also studied. Presented also is a mathematical model which could be used to predict automated sorter separation efficiency. All separation efficiency investigations were undertaken using a TiTech Combisense© (BSM 063) automated sorter. Samples of granite were sized into -20+15mm, -15+10mm and -10+6mm size fractions and grouped into cubic and flaky shape fractions. These fractions were then divided into two with one portion painted for colour separation efficiency investigations. The separation efficiency results confirmed earlier research indicating that particle size and the fraction requiring deflection affects separation efficiency, with separation efficiency decreasing with a decrease in particle size and an increase in throughput. It was observed that co-deflection loss occurs when correctly identified ‘accept’ particles are co-deflected due to their close proximity to ‘reject’ particles that are to be deflected. Observations from the tests indicate that an increase in the proportion of particles requiring deflection increases the probability of finding ‘accept’ particles in close proximity to ‘reject’ particles leading to co-deflections. Monte Carlo simulations were used to produce a random distribution of particles on the conveyor belt as would be obtained from actual investigations. From these simulations particle proximity relationships and particle co-deflections were studied. Results indicate that the Monte Carlo simulations under-predicts particle proximity associations. The effect of shape on co-deflection was investigated with results indicating that flaky shaped particles produce higher number of co-deflections compared to cubic shaped particles. It was also observed that the valve sensitivity determined from valve opening and closing times is of importance to the selectivity (precision) of the separating air jets. A mathematical separation efficiency model is presented which contains two variables, the belt loading (calculated using particle size, shape and throughput) and the particle fraction of the total test batch that are to be deflected (% deflection). The separation efficiency can be calculated once these two variables are determined.
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Ho, Yick Sing. "Modelling of the conical entrance oriface plate flow sensor." Thesis, City University London, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.357284.
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Lantto, Johanna, and Willie Wiholm. "Innovative communication strategies and modelling of robust sensor functions." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139941.
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The aim of this thesis was to create a resilient network, capable of handling link failures without affecting the data flow. This was done by using graph theory and three mathematical models. A generic system was created, on which the models were applied on. The mathematical models were path diversity, edge protection and path restoration. These models were tested to evaluate if they could create a robust system. The models were also compared with each other to obtain the best performing one. It was concluded that it was possible to construct a resilient network using these types of mathematical modelling. It was also concluded that the models provided different results in terms of cost and robustness. The report ends with suggestions on future work of how studies can be conducted to create realistic systems.
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Conlin, Adrian Keith. "Complex sensor data analysis through data augmentation." Thesis, University of Newcastle Upon Tyne, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320016.
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Moody, Leigh. "Sensors, measurement fusion and missile trajectory optimisation." Thesis, Cranfield University; College of Defence Technology; Department of Aerospace, Power and Sensors, 2003. http://hdl.handle.net/1826/778.
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When considering advances in “smart” weapons it is clear that air-launched
systems have adopted an integrated approach to meet rigorous requirements,
whereas air-defence systems have not. The demands on sensors, state
observation, missile guidance, and simulation for air-defence is the subject of
this research. Historical reviews for each topic, justification of favoured
techniques and algorithms are provided, using a nomenclature developed to unify these disciplines. Sensors selected for their enduring impact on future systems are described and simulation models provided. Complex internal systems are reduced to simpler models capable of replicating dominant features, particularly those that adversely effect state observers.
Of the state observer architectures considered, a distributed system comprising
ground based target and own-missile tracking, data up-link, and on-board
missile measurement and track fusion is the natural choice for air-defence. An
IMM is used to process radar measurements, combining the estimates from
filters with different target dynamics. The remote missile state observer
combines up-linked target tracks and missile plots with IMU and seeker data to
provide optimal guidance information.
The performance of traditional PN and CLOS missile guidance is the basis
against which on-line trajectory optimisation is judged. Enhanced guidance
laws are presented that demand more from the state observers, stressing the
importance of time-to-go and transport delays in strap-down systems
employing staring array technology. Algorithms for solving the guidance twopoint
boundary value problems created from the missile state observer output
using gradient projection in function space are presented.
A simulation integrating these aspects was developed whose infrastructure,
capable of supporting any dynamical model, is described in the air-defence
context. MBDA have extended this work creating the Aircraft and Missile
Integration Simulation (AMIS) for integrating different launchers and missiles.
The maturity of the AMIS makes it a tool for developing pre-launch algorithms
for modern air-launched missiles from modern military aircraft.
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Radford, Darren Lee James. "Fusion-based impairment modelling for an intelligent radar sensor architecture." Thesis, Cardiff University, 2009. http://orca.cf.ac.uk/54820/.
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An intelligent radar sensor concept has been developed using a modelling approach for prediction of sensor performance, based on application of sensor and environment models. Land clutter significantly impacts on the operation of radar sensors operating at low-grazing angles. The clutter modelling technique developed in this thesis for the prediction of land clutter forms the clutter model for the intelligent radar sensor. Fusion of remote sensing data is integral to the clutter modelling approach and is addressed by considering fusion of radar remote sensing data, and mitigation of speckle noise and data transmission impairments. The advantages of the intelligent sensor approach for predicting radar performance are demonstrated for several applications using measured data. The problem of predicting site-specific land radar performance is an important task which is complicated by the peculiarities and characteristics of the radar sensor, electromagnetic wave propagation, and the environment in which the radar is deployed. Airborne remote sensing data can provide information about the environment and terrain, which can be used to more accurately predict land radar performance. This thesis investigates how fusion of remote sensing data can be used in conjunction with a sensor modelling approach to enable site-specific prediction of land radar performance. The application of a radar sensor model and a priori information about the environment, gives rise to the notion of an intelligent radar sensor which can adapt to dynamically changing environments through intelligent processing of this a priori knowledge. This thesis advances the field of intelligent radar sensor design, through an approach based on fusion of a priori knowledge provided by remote sensing data, and application of a modelling approach to enable prediction of radar sensor performance. Original contributions are made in the areas of intelligent radar sensor development, improved estimation of land surface clutter intensity for site-specific low-grazing angle radar, and fusion and mitigation of sensor and data transmission impairments in radar remote sensing data.
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Manninen, O. (Olli). "Modelling the antenna arrays using MATLAB-application Sensor Array Analyzer." Bachelor's thesis, University of Oulu, 2017. http://urn.fi/URN:NBN:fi:oulu-201705302196.
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In this thesis, the antenna arrays researched and modelled using Sensor Array Analyzer- application (SAA) from MATLAB. The objective is to explore the array modelling capabilities of the SAA application. This thesis shows that SAA is versatile software for modelling the radiation patterns using 2D or 3D plots, but there are couple of missing features. SAA allows user to import the used code to MATLAB for code modification. Data imported from MATLAB to SAA using variables, for example importing dipole, antenna locations for conformal array and complex coefficients for beamforming. Antenna array wideband usage at SAA discussed and example shown. At SAA, grating lobes seen at 2D and 3D plots and grating lobe- diagram is also used and explained. SAA has no built-in option for mutual coupling compensation. Other practical method for modelling and compensation of mutual coupling are discussedTässä kandidaatintyössä tutkittiin eri geometrian omaavia antenniryhmiä ja niiden mallinnusta MATLAB-ohjelmiston lisäosan SAA:n (Sensor Array Analyzer) avulla. Tehtävänä oli tutkia antenniryhmän eri osa-alueiden mallinnuksen mahdollisuuksia ja rajoituksia kyseisellä ohjelmistolla. Tutkimuksen tuloksena todetaan, että SAA on monipuolinen ohjelmisto antenniryhmien säteilykuvioiden graafiseen havainnollistamiseen 2D- tai 3D-muodossa, vaikkakin muutama perusominaisuus puuttui. Työssä tutkittiin, miten SAA-ohjelmistosta voidaan siirtää käytetty koodi MATLAB-ohjelmistoon sen mahdollista lisämuokkausta varten ja kuinka MATLAB-ohjelmistosta tuodaan tietoa SAA-ohjelmistoon erilaisina muuttujina. Muuttujia tarvitaan esimerkiksi, kun ohjelmistoon tuodaan antennin säteilykuvio, tai sovellettu antenniryhmä sekä niiden kompleksiset kertoimet keilanmuodostusta varten. Laajakaistaisten antenniryhmien säteilykuvion mallinnusta testattiin ja havainnollistettiin. Sivukeiloja, joilla on sama teho pääkeilan kanssa, tarkasteltiin ja niiden havainnollistamiseen luotua diagrammia testattiin. Antennien välisen keskinäiskytkennän mallintamisen mahdollisuuksia tarkasteltiin ja sen vaikutusta säteilykuvioon pohdittiin. Tämän työn tarkoituksena oli selvittää SAA-ohjelmiston pääpiirteiset ominaisuudet ja heikkoudet. Kyseistä tietoa käytetään antenniryhmien keilasynteesiä tutkiessa. Antenniryhmiä voi mallintaa huomattavasti nopeammin ja helpommin käyttämällä SAA-ohjelmistoa, kuin kirjoittamalla itse MATLAB-koodi tai simuloimalla antenniryhmän sähkömagneettinen 3D-malli. Ohjelmiston heikkoudetkin voidaan välttää muokkaamalla koodia haluamalla tavalla. Antenniryhmiä tullaan tulevaisuudessa hyödyntämään IoT-laitteissa ja langattomassa 5G teknologiassa
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Merrett, Geoff V. "Energy- and information-managed wireless sensor networks : modelling and simulation." Thesis, University of Southampton, 2008. https://eprints.soton.ac.uk/65002/.
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Wireless Sensor Networks (WSNs) allow the remote and distributed monitoring of parameters in their deployed environment. WSNs are receiving increasing research interest, due to their ability to enable a wide range of applications, and their potential to have a major impact on ubiquitous computing. Many research challenges are encountered in retaining a useful network lifetime under constrains imposed by the limited energy reserves that are inherent in the small, locally-powered sensor nodes. This research addresses some of these challenges through the development and evaluation of energy- and information-managed algorithms leading to increased network lifetime. The first contribution of this research is the development of an Information manageD Energy-aware ALgorithm for Sensor networks with Rule Managed Reporting (IDEALS/RMR). IDEALS/RMR is an application-independent, localised system to control and manage the degradation of a network through the positive discrimination of packets. This is achieved by the novel combination of energy management (through IDEALS) and information management (through RMR) which increases the network lifetime at the possible expense of often trivial data. IDEALS/RMR is particularly suited to applications where sensor nodes are small, energy constrained, embedded devices particularly those that feature energy harvesting) that are required to report data in an unassisted fashion. The second contribution of this research is the analysis of various environmental and physical aspects of WSNs, and the effect that they have on the operation of nodes and networks. These aspects include energy components (stores, sources and consumers), sensing devices, wireless communication, and timing; these aspects are independently modelled and, through simulation, their effect on the operation of the network is quantified. The third contribution of this research is the evaluation of IDEALS/RMR using a simulator that has been specifically developed to integrate both the proposed environmental and physical models, and a novel node architecture that facilitates structured software design. A scenario depicting the use of a WSN to monitor pump temperature in a water pumping station is simulated, and highlights the benefits of the developed algorithms.
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Matos, Gabriel Silva de. "Laser triangulation sensor with refraction modelling for underwater 3D measurement." reponame:Repositório Institucional da UFSC, 2017. https://repositorio.ufsc.br/xmlui/handle/123456789/182608.
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Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Mecânica, Florianópolis, 2017.Made available in DSpace on 2018-01-09T03:24:39Z (GMT). No. of bitstreams: 1 348525.pdf: 5019460 bytes, checksum: 4ed315a3b59a2bab9c3e13fc079bb513 (MD5) Previous issue date: 2017
Medições tridimensionais subaquáticas possuem diversas aplicações, por exemplo, na indústria de petróleo e gás para o controle de equipamentos submarinos durante procedimentos de manutenção otimizados. Sistemas com sensores de triangulação a laser (LTS) já são utilizados em ambientes subaquáticos e alguns desafios com LTS nestes ambientes já foram discutidos. Entre estes obstáculos estão a má qualidade de imagem, devido à absorção de luz e retrodifusão, e refração, devido às interfaces entre água e vidro e vidro e ar. O efeito da refração pode ser modelado conhecendo-se a distância da câmera à superfície de refração, o eixo de refração, o índice de refração dos meios e a espessura da janela óptica. Este trabalho analisa dois métodos para a calibração subaquática de LTS com experimentos em laboratório utilizando um LTS desenvolvido para esta aplicação. O primeiro método utiliza um ajuste polinomial, correlacionando o pico do laser para cada linha da imagem da câmera com um ponto 3D. Este método necessita de uma calibração subaquática completa. O segundo método, proposto aqui, é baseado no modelo de câmera pinhole e um plano matemático ajustado para o plano de luz laser projetado. Em medições de ar, para cada pico de laser detectado na imagem, uma linha pode ser definida através do centro da lente aplicando a matriz de projeção do modelo pinhole. A intersecção desta linha com o plano laser matemático resulta na medição de um ponto 3D. Para medições subaquáticas com um LTS de alta qualidade é necessário considerar, adicionalmente, o efeito da refração na interface entre a janela e água. Considerando a janela óptica normal ao eixo da câmera, um caminho de raio é definido no plano de refração de acordo com a lei de Snell para interceptar o plano do laser, definindo um ponto 3D. A calibração para medição subaquática necessita, portanto, estimar a distância da superfície de refração até o centro óptico da câmera. No método proposto, após a calibração no ar, um degrau é medido embaixo d'água e a distância da janela da câmera é otimizada. O método é avaliado de acordo com as diretrizes do VDI / VDE 2634 e vários objetos foram utilizados como exemplos de medição.
Abstract : Underwater tridimensional measurement has many applications, for example, to control underwater equipment during optimized maintenance procedures in the oil and gas industry. Systems with laser triangulation sensors (LTS) are being used underwater at present and some underwater problems with LTS have already been discussed. Among these challenging obstacles are poor image quality, due to light absorption and backscattering, and refraction, due to optical window interfaces between water and air inside the camera chamber. The refraction effect can be predicted knowing the distance from the camera pinhole center to the surface of refraction, the axis of refraction, the refractive index of the mediums and the thickness of the optical window. This work analyses two methods for underwater LTS calibration using real experiments with a built LTS, in-air and underwater. The first method uses a polynomial adjustment correlating to the laser peak for each camera image line with a 3D point. This method needs a complete calibration in the underwater environment. The second method proposed is based on the pinhole camera model and a fitted mathematical plane for the projected laser light plane. In air measurements, a line can be defined through the lens center using the pinhole projection matrix for each laser peak detected in the image. The intersection of this line with the laser mathematical plane leads to a measured 3Dpoint. For high quality underwater LTS measurements, it is necessary to additionally consider the refraction effect on the window and water interface. Considering the optical window normal to the camera axis, a ray path is defined on the plane of refraction according to the Snell?s law to intercept the laser plane, defining a 3D point. The calibration for underwater measurement needs to estimate the window distance from the camera. In the proposed method, after the in-air calibration,a step standard is measured underwater and the window distance from the camera is optimized. The method is evaluated according to the guidelines of VDI/VDE 2634 and multiple objects were evaluated.
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Ambarek, A. H. "Models of olfactory sensors." Thesis, University of Exeter, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.379681.
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Koo, Sung-Han. "Forecasting fire development with sensor-linked simulation." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/4187.
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In fire, any information about the actual condition within the building could be essential for quick and safe response of both fire–fighters and occupants. In most cases, however, the emergency responders will rarely be aware of the actual conditions within a building and they will have to make critical decisions based on limited information. Recent buildings are equipped with numbers of sensors which may potentially contain useful information about the fire; however, most buildings do not have capability of exploiting these sensors to provide any useful information beyond the initial stage of warning about the possible existence of a fire. A sensor–linked modelling tool for live prediction of uncontrolled compartment fires, K– CRISP, has therefore been developed. The modelling strategy is an extension of the Monte– Carlo fire model, CRISP, linking simulations to sensor inputs which controls evolution of the parametric space in which new scenarios are generated, thereby representing real–time “learning” about the fire. CRISP itself is based on a zone model representation of the fire, with linked capabilities for egress modelling and failure prediction for structural members, thus providing a major advantage over more detailed approaches in terms of flexibility and practicality, though with the conventional limitations of zone models. Large numbers of scenarios are required, but computational demands are mitigated to some extent by various procedures to limit the parameters which need to be varied. HPC (high performance computing) resources are exploited in “urgent computing” mode. K–CRISP was demonstrated in conjunction with measurements obtained from two sets of full–scale fire experiments. In one case, model execution was performed live. The thesis further investigates the predictive capability of the model by running it in pseudo real–time. The approach adopted for steering is shown to be effective in directing the evolution of the fire parameters, thereby driving the fire predictions towards the measurements. Moreover, the availability of probabilistic information in the output assists in providing potential end users with an indication of the likelihood of various hazard scenarios. The best forecasts are those for the immediate future, or for relatively simple fires, with progressively less confidence at longer lead times and in more complex scenarios. Given the uncertainties in real fire development the benefits of more detailed model representations may be marginal and the system developed thus far is considered to be an appropriate engineering approach to the problem, providing information of potential benefit in emergency response. Thus, the sensor–linked model proved to be capable of forecasting the fire development super–real– time and it was also able to predict critical events such as flashover and structural collapse. Finally, the prediction results are assessed and the limitations of the model were further discussed. This enabled careful assessment of how the model should be applied, what sensors are required, and how reliable the model can be, etc.
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Al, Jowder Raed Ebrahim. "Investigation on different luminophores and sensor modelling techniques for gas sensing." Thesis, University of Manchester, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.503048.
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Clare, Anthony Joseph. "Real-time modelling and sensor fusion for a synthetic vision system." Thesis, University of Sheffield, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.434515.
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Barbosa, Pedro. "Scalable wireless sensor networks for dynamic communication environments : simulation and modelling." Thesis, University of Southampton, 2011. https://eprints.soton.ac.uk/177575/.
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This thesis explores the deployment of Wireless Sensor Networks (WSNs) on localised maritime events. In particular, it will focus on the deployment of a WSN at sea and estimating what challenges derive from the environment and how they affect communication. This research addresses these challenges through simulation and modelling of communication and environment, evaluating the implications of hardware selection and custom algorithm development. The first part of this thesis consists of the analysis of aspects related to the Medium Access Control layer of the network stack in large-scale networks. These details are commonly hidden from upper layers, thus resulting in misconceptions of real deployment characteristics. Results show that simple solutions have greater advantages when the number of nodes within a cluster increases. The second part considers routing techniques, with focus on energy management and packet delivery. It is shown that, under certain conditions, relaying data can increase energy savings, while at the same time allows a more even distribution of its usage between nodes. The third part describes the development of a custom-made network simulator. It starts by considering realistic radio, channel and interference models to allow a trustworthy simulation of the deployment environment. The MAC and Routing techniques developed thus far are adapted to the simulator in a cross-layer manner. The fourth part consists of adapting the WSN behaviour to the variable weather and topology found in the chosen application scenario. By analysing the algorithms presented in this work, it is possible to find and use the best alternative under any set of environmental conditions. This mechanism, the environment-aware engine, uses both network and sensing data to optimise performance through a set of rules that involve message delivery and distance between origin and cluster head
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Sallinen, Mikko. "Modelling and estimation of spatial relationships in sensor-based robot workcells /." Espoo [Finland] : VTT Technical Research Centre of Finland, 2003. http://www.vtt.fi/inf/pdf/publications/2003/P509.pdf.
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Xu, Yangdi. "Unsupervised daily indoor routine modelling using a single RGGB-D sensor." Thesis, University of Bristol, 2017. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.743023.
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Ollander, Simon. "Wearable Sensor Data Fusion for Human Stress Estimation." Thesis, Linköpings universitet, Reglerteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-122348.
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With the purpose of classifying and modelling stress, different sensors, signal features, machine learning methods, and stress experiments have been compared. Two databases have been studied: the MIT driver stress database and a new experimental database, where three stress tasks have been performed for 9 subjects: the Trier Social Stress Test, the Socially Evaluated Cold Pressor Test and the d2 test, of which the latter is not classically used for generating stress. Support vector machine, naive Bayes, k-nearest neighbor and probabilistic neural network classification techniques were compared, with support vector machines achieving the highest performance in general (99.5 ±0.6 %$on the driver database and 91.4 ± 2.4 % on the experimental database). For both databases, relevant features include the mean of the heart rate and the mean of the galvanic skin response, together with the mean of the absolute derivative of the galvanic skin response signal. A new feature is also introduced with great performance in stress classification for the driver database. Continuous models for estimating stress levels have also been developed, based upon the perceived stress levels given by the subjects during the experiments, where support vector regression is more accurate than linear and variational Bayesian regression.I syfte att klassificera och modellera stress har olika sensorer, signalegenskaper, maskininlärningsmetoder och stressexperiment jämförts. Två databaser har studerats: MIT:s förarstressdatabas och en ny databas baserad på egna experiment, där stressuppgifter har genomförts av nio försökspersoner: Trier Social Stress Test, Socially Evaluated Cold Pressor Test och d2-testet, av vilka det sistnämnda inte normalt används för att generera stress. Support vector machine-, naive Bayes-, k-nearest neighbour- och probabilistic neural network-algoritmer har jämförts, av vilka support vector machine har uppnått den högsta prestandan i allmänhet (99.5 ± 0.6 % på förardatabasen, 91.4 ± 2.4 % på experimenten). För båda databaserna har signalegenskaper såsom medelvärdet av hjärtrytmen och hudens ledningsförmåga, tillsammans med medelvärdet av beloppet av hudens ledningsförmågas derivata identifierats som relevanta. En ny signalegenskap har också introducerats, med hög prestanda i stressklassificering på förarstressdatabasen. En kontinuerlig modell har också utvecklats, baserad på den upplevda stressnivån angiven av försökspersonerna under experimenten, där support vector regression har uppnått bättre resultat än linjär regression och variational Bayesian regression.
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Sayginer, Osman. "Modelling and simulation of novel optoacoustic sensors for monitoring crack growth in pressure vessel steels." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/304021.
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The acoustic emission technique is an effective way to acquire crack information from material bodies at the microscopic level. Monitoring of the acoustic emission events provides a deeper understanding regarding the structural health status of critical constructions such as bridges, railways, pipelines, pressure vessels, etc. Thanks to the acoustic emission monitoring systems, it is possible to avoid catastrophic events and save lives, time, and money. For this reason, efforts to develop new acoustic emission sensor technologies, as well as the use of current acoustic emission sensors in new research fields, will contribute to the limited literature sources.
Optical sensing systems provide good alternatives to the existing sensing technologies because of their wide range of detection bandwidths, adaptation to harsh environments, and low sensitivity to electromagnetic interference. For this reason, the first part of this thesis demonstrates an optoacoustic sensing methodology that enables the detection of acoustic emissions by optics. This sensing system consists of thin-film optical filters (TFOF) and an elastic microcavity layer. The sensing mechanism is similar to the Fabry Perot structures and it relies on resonance shifts of the cavity when there is a change in the cavity thickness similar to the Fabry Perot structures. Thus, the design, fabrication, and demonstration steps of a Fabry Perot elastic microcavity have been presented. Throughout the fabrication efforts, a new deposition protocol was developed. This deposition technique has enabled the deposition of TFOF on flexible substrates via the RF-sputtering technique. Thus, a new sensing configuration has been developed using flexible optical components.
In the second chapter, an optical sensing methodology based on tunable spectral filters and flexible optical components is introduced. The design, fabrication, realization, and characterization of a proof-of-concept optomechanical sensor have been presented. The design step includes optical, mechanical, and optoacoustic correlation simulations using the Transfer Matrix Method, finite element analysis, and analytical models. Moreover, the fabrication part includes multilayer deposition on silica and flexible substrates using the RF-Sputtering technique and integration of these optical components into a 3D-printed housing together with electronic components. Eventually, the performance evaluation of the optomechanical sensor has been carried out and the experimental results showed that the sensor resonance frequency is around 515 Hz and the sensor is capable of detecting static loadings from 50 Pa to 235 Pa values.
In the fourth chapter, seismic vulnerability analysis of a coupled Tank-Piping System has been performed using traditional acoustic emission sensors. Real-time performance evaluation of the pipeline as well as the structural health status of the critical parts were monitored. As a result, deformation levels of each critical part were investigated, and the processing of acoustic emission signals provided a more in-depth view of damage level of the analyzed components.
Throughout the thesis, TFOFs are an integral part of this thesis. Therefore, both the design and simulation of TFOFs play a crucial role throughout this research work. The Transfer Matrix Method is used to simulate the optical performance of TFOFs.
Moreover, in the final chapter, an automated design framework is presented for the design of TFOFs using a nature-inspired machine learning approach called Genetic algorithm. This design approach enables the design of sophisticated geometric configurations with unique optical capabilities. Therefore, not only the improvement of sensor response but also the new ways in the development of novel optical systems are demonstrated in this final chapter.
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Mesbahi, Ehsan. "Artificial neural networks for fault diagnosis, modelling and control of diesel engines." Thesis, University of Newcastle Upon Tyne, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323447.
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Zhai, Jianhua. "Design, Modelling and Simulation of a Wireless Pressure Sensor for Medical Applications." Thesis, University of Liverpool, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.507475.
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Wu, Yan. "Propagation modelling for wireless sensor networks deployed to perform civil infrastructure monitoring." Thesis, University of Cambridge, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.608685.
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Van, der Merwe S. "Modelling and performance evaluation of a three-phase capacitive voltage sensor topology." Thesis, Stellenbosch : University of Stellenbosch, 2006. http://hdl.handle.net/10019.1/2032.
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Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2006.This research project investigates the design, modelling and application of an open-air capacitive voltage sensor assembly for the measurement of wideband High Voltage signals on three-phase transmission lines. The advantages and disadvantages of conventional methods used to measure these voltages are reviewed and the advantages of the open-air capacitive sensor are established. The main research objective of this project involves extending the application of previously developed single-phase capacitive sensor topologies to three-phase applications. A three-phase set of mobile, compact and relatively inexpensive capacitive voltage sensors for open-air application under overhead transmission lines are designed and constructed, including a data acquisition triggering system for the measurement of transient waveforms. Equivalent circuit models, using a Thévenin equivalent approach, are developed for the three-phase sensor topology and the associated three-phase transmission line configuration. A number of different methods for simplifying the associated Thévenin equivalent impedance and voltage equations are evaluated. The decoupling of the voltage waveforms measured by the individual sensors for a three-phase transmission line configuration is subsequently examined with the view to derive mathematical relationships for determining the phase conductor voltages from the measured sensor voltages. The performance of the sensor assembly is experimentally evaluated under laboratory conditions as well as field conditions. An outdoor HV test facility, representing a scaled three-phase flat transmission line structure, is developed for evaluation of the three-phase sensor topology in a controlled environment. The methodology for decoupling the phase voltages and reconstructing the phase conductor voltages from the voltages induced on the sensors is evaluated using measured data obtained with this HV test facility. It is shown that the three-phase capacitive voltage sensor topology as applied in the test facility delivers good results for the measurement of three-phase transient voltage waveforms.
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Aloufi, Mansour. "Response surface modelling and performance optimisation of energy harvester-powered sensor nodes." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/355882/.
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The emerging technologies of harvesting the energy from the environment surrounding the application have recently attracted intensive attention of design automation researchers.Due to the universal presence of vibrations on machines, among the different mechanisms available to obtain electrical power from ambient energy, the vibration basedharvesters have been the subject of particularly extensive development. A vibration-based (kinetic) harvester simply converts vibrations in the environment surrounding a wireless sensor node into electrical energy. This enables the wireless sensor node to be placed anywhere in the environment with no need for access to facilitate battery replacement. The basic structure of vibration-based energy harvester is composed of multi-domain components, it contains electrical, mechanical, and magnetic in the case of electromagnetic harvester. In addition, many design parameters from different domains need to be optimised in a holistic manner (i.e. treating all the system components as a connected unit); all these requirements besides the traditional approaches of optimisation, complicate the hardware description language for analog and mixed syste (HDL-AMS) simulation and makes central processor unit (CPU) takes prohibitive time, even with today's multi-physics simulation tools. This research develops, a novel optimisation technique, which enables effcient optimisation and design exploration for such a complex system and reduce CPU computation time for optimisation purposes. The proposed methodology accelerates the optimisation by approximately two orders of magnitude due to the utilisation of the design of experiment (DoE) approach and response surface modelling (RSM). The contributions of this research can be summarised as follows: Firstly, a novel, response surface based design space exploration approach to energy harvester powered systems has been developed. The proposed technique enables designers to gain insight into the details of design parameters trade-offs and quantifies each design parameter effect on performance indicators via the response surface mathematical model. The method has been applied to a linear micro-electromagnetic cantilevered harvester. Secondly, a novel, fast performance optimisation technique for a wireless sensor node powered by a tunable kinetic energy harvester has been developed. The result of applying this technique reduces the total CPU optimisation time by two orders of magnitude compared with the classical approach, i.e. through multiple full simulations. Thirdly, a software tool set has been created, based on MATLAB and VHDL-AMS, for fast, multi-dimensional design space exploration and optimisation of a kinetic harvester
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Ma, Chao. "Performance modelling and analysis of multiple coexisting IEEE 802.15.4 wireless sensor networks." Thesis, Aston University, 2014. http://publications.aston.ac.uk/23473/.
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With the features of low-power and flexible networking capabilities IEEE 802.15.4 has been widely regarded as one strong candidate of communication technologies for wireless sensor networks (WSNs). It is expected that with an increasing number of deployments of 802.15.4 based WSNs, multiple WSNs could coexist with full or partial overlap in residential or enterprise areas. As WSNs are usually deployed without coordination, the communication could meet significant degradation with the 802.15.4 channel access scheme, which has a large impact on system performance. In this thesis we are motivated to investigate the effectiveness of 802.15.4 networks supporting WSN applications with various environments, especially when hidden terminals are presented due to the uncoordinated coexistence problem. Both analytical models and system level simulators are developed to analyse the performance of the random access scheme specified by IEEE 802.15.4 medium access control (MAC) standard for several network scenarios. The first part of the thesis investigates the effectiveness of single 802.15.4 network supporting WSN applications. A Markov chain based analytic model is applied to model the MAC behaviour of IEEE 802.15.4 standard and a discrete event simulator is also developed to analyse the performance and verify the proposed analytical model. It is observed that 802.15.4 networks could sufficiently support most WSN applications with its various functionalities. After the investigation of single network, the uncoordinated coexistence problem of multiple 802.15.4 networks deployed with communication range fully or partially overlapped are investigated in the next part of the thesis. Both nonsleep and sleep modes are investigated with different channel conditions by analytic and simulation methods to obtain the comprehensive performance evaluation. It is found that the uncoordinated coexistence problem can significantly degrade the performance of 802.15.4 networks, which is unlikely to satisfy the QoS requirements for many WSN applications. The proposed analytic model is validated by simulations which could be used to obtain the optimal parameter setting before WSNs deployments to eliminate the interference risks.
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Trenggono, Praditio Putra. "Statistical modelling of wind effects on signal propagation for wireless sensor networks." Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/49841/1/Praditio_Trenggono_Thesis.pdf.
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A wireless sensor network system must have the ability to tolerate harsh environmental conditions and reduce communication failures. In a typical outdoor situation, the presence of wind can introduce movement in the foliage. This motion of vegetation structures causes large and rapid signal fading in the communication link and must be accounted for when deploying a wireless sensor network system in such conditions.
This thesis examines the fading characteristics experienced by wireless sensor nodes due to the effect of varying wind speed in a foliage obstructed transmission path. It presents extensive measurement campaigns at two locations with the approach of a typical wireless sensor networks configuration. The significance of this research lies in the varied approaches of its different experiments, involving a variety of vegetation types, scenarios and the use of different polarisations (vertical and horizontal).
Non–line of sight (NLoS) scenario conditions investigate the wind effect based on different vegetation densities including that of the Acacia tree, Dogbane tree and tall grass. Whereas the line of sight (LoS) scenario investigates the effect of wind when the grass is swaying and affecting the ground-reflected component of the signal. Vegetation type and scenarios are envisaged to simulate real life working conditions of wireless sensor network systems in outdoor foliated environments.
The results from the measurements are presented in statistical models involving first and second order statistics. We found that in most of the cases, the fading amplitude could be approximated by both Lognormal and Nakagami distribution, whose m parameter was found to depend on received power fluctuations. Lognormal distribution is known as the result of slow fading characteristics due to shadowing.
This study concludes that fading caused by variations in received power due to wind in wireless sensor networks systems are found to be insignificant. There is no notable difference in Nakagami m values for low, calm, and windy wind speed categories. It is also shown in the second order analysis, the duration of the deep fades are very short, 0.1 second for 10 dB attenuation below RMS level for vertical polarization and 0.01 second for 10 dB attenuation below RMS level for horizontal polarization. Another key finding is that the received signal strength for horizontal polarisation demonstrates more than 3 dB better performances than the vertical polarisation for LoS and near LoS (thin vegetation) conditions and up to 10 dB better for denser vegetation conditions.
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Prache, Pierre. "Modelling, design and integration of new differential architectures for M/NEMS resonant sensors." Doctoral thesis, Universitat Autònoma de Barcelona, 2017. http://hdl.handle.net/10803/458025.
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Los sensores M/NEMS resonantes, gracias a su pequeño tamaño, a su bajo consumo y a su carácter quasi-digital (siendo generalmente la señal de salida un tono frecuencial), se han convertido en herramientas muy usadas en sistemas embebidos portátiles y de a bordo tales como en telefonía móvil (es decir, en smartphones) o en la industria aeroespacial. Sin embargo, dichos sensores sufren desajustes provenientes de perturbaciones del entono que les rodea y, a pesar de la posibilidad de disminuir tales efectos mediante el uso de diferentes técnicas, en según qué escenarios, es imperativo el uso de arquitecturas diferenciales para remover tales desajustes y así asegurar un correcto y fiable funcionamiento incluso en los entornos más severos en cuanto a perturbaciones.
En esta tesis se estudia una novedosa técnica de medida diferencial, que consiste en sincronizar dos resonadores, uno siendo una referencia y el otro actuando como sensor. Ambos resonadores oscilan a la misma frecuencia estando en un mismo lazo realimentado. Cuando se produce un desajuste entre ambos, procedente de la magnitud física a medir, se genera un desfase. Tal desfase permite teóricamente capturar la magnitud física a medir totalmente libre de desajustes procedentes de perturbaciones externas. Además, esta técnica es fácilmente integrable, lo cual la hace un candidato prometedor para su futura integración a gran escala.
Después del estudio del marco teórico de la sincronización de resonadores, varias directrices se plantean para el diseño de tal arquitectura, las cuales se usan para realizar la fabricación de un prototipo para probar el concepto. Dicho prototipo se caracteriza experimentalmente y se comprara con los resultados teóricos calculados inicialmente, mostrando muy buen ajuste, con una mejora de la sensibilidad del orden del factor de calidad Q de los resonadores MEMS, y un thermal drift rejection ratio del orden de 200.M/NEMS resonant sensors, due to their small size, consumption and quasi-digital output (a frequency most of the time) are useful tools for on-board systems, from smartphones to aeronautic technology. However, they suffer from environmental drifts, and even though the effect of these drifts can be limited by the design, it is sometimes necessary to use differential architectures to properly remove the drifts from the measurements and ensure the output reliability even in harsh environments. In this work, a special technique for differential measurement is studied and implemented, consisting in the synchronization of two resonators, one reference and one sensor. Placed in a single feedback loop, they oscillate at the same frequency and eventual phase shift when the physical quantity to be sensed is applied. This phase shift is a theoretically drift-free way to measure this physical quantity. This technique also benefits from its ease of integration, making it a good candidate for large scale integration. After studying the theoretical framework of the synchronization of two resonators, several design guidelines are found for the architecture, which are used in the fabrication of a proof of concept. The theoretical performances are found as well, and compared to the experimental ones. A very good agreement is found between experiment and theory, with a sensitivity enhancement of the order of the MEMS resonators quality factor, and a thermal drift rejection ratio of the order of 200.
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Chapman, Timothy Peter. "Morphological and neural modelling of the orthopteran escape response." Thesis, University of Stirling, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.391494.
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Kloos, Gerold. "Radio-Frequency Signal Strength Based Localisation in Unstructured Outdoor Environments." Faculty of Engineering and Information Technologies, 2008. http://hdl.handle.net/2123/2242.
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Doctor of Philosophy (PhD)This thesis addresses the issues arising in range-only localisation and tracking using Radio Frequency Received Signal Strength Indicator measurements. One of the key issues in Radio Frequency (RF) based localisation and tracking applications is to obtain an accurate sensor representation. Such a sensor model is one of the prerequisites to achieve high accuracy and precision in the localisation and tracking task. The sensor models used at present for this task are very simplistic, and as a consequence are unable to achieve highly accurate and precise localisation. While such an accurate sensor description is desirable it has not been presented for RF sensors. This thesis addresses the task of obtaining an accurate sensor model for RF sensors. The major drawbacks of the most commonly used model, the nth power model, are demonstrated. A new model to satisfy the necessary requirements for high accuracy localisation is developed. This model is based on theoretical considerations and experimental data. It depicts the real occurring behaviour of RF sensors more closely than the models used so far for RF based range-only localisation. The use of this better sensor representation offers the possibility of achieving more accurate localisation. The expected performance of the alternative sensor model is compared to the commonly used nth power model. Furthermore, the inherent properties of the new sensor model are presented and their ramifications with regards to the goal of achieving highly accurate localisation are discussed. In addition to the sensor model development, the well-known probabilistic filtering techniques Kalman Filter, Particle Filter and Histogram Filter are compared and used to implement 1-dimensional and 2-dimensional range-only trackers. The filtering techniques are evaluated with respect to their suitability for appropriately handling the new multi-modal sensor model and the resulting multi-modal state distributions, and to provide correct and conclusive localisation and tracking results. Results from experiments using real data obtained in outdoor environments with a prototype RF localisation system as well as results obtained from simulations are presented in this thesis to validate the theoretical findings and the newly developed sensor model.
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Kloos, Gerold. "Radio-Frequency Signal Strength Based Localisation in Unstructured Outdoor Environments." Thesis, The University of Sydney, 2007. http://hdl.handle.net/2123/2242.
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This thesis addresses the issues arising in range-only localisation and tracking using Radio Frequency Received Signal Strength Indicator measurements. One of the key issues in Radio Frequency (RF) based localisation and tracking applications is to obtain an accurate sensor representation. Such a sensor model is one of the prerequisites to achieve high accuracy and precision in the localisation and tracking task. The sensor models used at present for this task are very simplistic, and as a consequence are unable to achieve highly accurate and precise localisation. While such an accurate sensor description is desirable it has not been presented for RF sensors. This thesis addresses the task of obtaining an accurate sensor model for RF sensors. The major drawbacks of the most commonly used model, the nth power model, are demonstrated. A new model to satisfy the necessary requirements for high accuracy localisation is developed. This model is based on theoretical considerations and experimental data. It depicts the real occurring behaviour of RF sensors more closely than the models used so far for RF based range-only localisation. The use of this better sensor representation offers the possibility of achieving more accurate localisation. The expected performance of the alternative sensor model is compared to the commonly used nth power model. Furthermore, the inherent properties of the new sensor model are presented and their ramifications with regards to the goal of achieving highly accurate localisation are discussed. In addition to the sensor model development, the well-known probabilistic filtering techniques Kalman Filter, Particle Filter and Histogram Filter are compared and used to implement 1-dimensional and 2-dimensional range-only trackers. The filtering techniques are evaluated with respect to their suitability for appropriately handling the new multi-modal sensor model and the resulting multi-modal state distributions, and to provide correct and conclusive localisation and tracking results. Results from experiments using real data obtained in outdoor environments with a prototype RF localisation system as well as results obtained from simulations are presented in this thesis to validate the theoretical findings and the newly developed sensor model.
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Raghavan, Rambali Sundara. "Optimisation of fluidised bed drying using electrical capacitance tomography sensor modelling and measurement." Thesis, University of Manchester, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.493952.
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The aim of this research was the development of an accurate, robust and reliable electrical capacitance tomography (ECT) sensor for the online measurement of solids concentration and moisture content profiles of fluidised bed dryers. In the pharmaceutical industry, fluidised bed dryers are used to dry wet particles prior to compression. Although electrical capacitance tomography (ECT) has been traditionally used to obtain images of the fluidisation processes, in this research, capacitance measurements from an ECT sensor mounted on a lab-scale fluidised bed dryer were used to estimate solids concentration and moisture content profiles. The effects of the process parameters, such as particle size, gas velocity, inlet gas temperature and relative humidity, on the moisture content of solids in the batch fluidlsed bed have been analysed theoretically.
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Eftaxias, Konstantinos. "Combined brain connectivity and cooperative sensor networks for modelling movement related cortical activities." Thesis, University of Surrey, 2016. http://epubs.surrey.ac.uk/810378/.
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The elucidation of the brain’s anatomical and functional organisation during specific tasks is a challenging field in modern brain research. There is also a growing interest in the field of brain connectivity and its relation to specific motor and mental tasks, as well as neurodegenerative diseases like Parkinson’s and Alzheimer’s. In this thesis, a novel approach for modelling motor tasks is proposed. This approach combines diffusion adaptation and brain connectivity measures in order to build models which describe complex tasks through time and space. In particular, an S-transform based measure is introduced to estimate the connectivity on single-trial basis. The connectivity values, corresponding to different frequency bands across time, are effectively coupled with diffusion adaptation. The diffusion strategy exploits the time-space characteristics in a distributed and collaborated manner, and leads to an enhanced model for motor or mental tasks. Specifically, the imaginary part of S-transform coherency is introduced as an EEG connectivity measure. The performance improvement over the existing connectivity measures on a single-trial basis is demonstrated. Moreover, diffusion Kalman filtering is used as it performs well for nonstationary problems like this. This novel method is tested on various scenarios. Initially, its performance is demonstrated for simulated datasets which are based on realistic scenarios. Then, the method is applied to two datasets of real data. The first set of experiments includes a complex motor task of clockwise and anticlockwise hand movement and the second set includes a multi-modal dataset acquired from Parkinson’s patients. The results show that the connectivity enhanced modelling outperforms the simple case where connectivity information is ignored, and can build a robust task-related model.
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Asadi, Sahar. "Towards Dense Air Quality Monitoring : Time-Dependent Statistical Gas Distribution Modelling and Sensor Planning." Doctoral thesis, Örebro universitet, Institutionen för naturvetenskap och teknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-61113.
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This thesis addresses the problem of gas distribution modelling for gas monitoring and gas detection. The presented research is particularly focused on the methods that are suitable for uncontrolled environments. In such environments, gas source locations and the physical properties of the environment, such as humidity and temperature may be unknown or only sparse noisy local measurements are available. Example applications include air pollution monitoring, leakage detection, and search and rescue operations. This thesis addresses how to efficiently obtain and compute predictive models that accurately represent spatio-temporal gas distribution. Most statistical gas distribution modelling methods assume that gas dispersion can be modelled as a time-constant random process. While this assumption may hold in some situations, it is necessary to model variations over time in order to enable applications of gas distribution modelling for a wider range of realistic scenarios. This thesis proposes two time-dependent gas distribution modelling methods. In the first method, a temporal (sub-)sampling strategy is introduced. In the second method, a time-dependent gas distribution modelling approach is presented, which introduces a recency weight that relates measurement to prediction time. These contributions are presented and evaluated as an extension of a previously proposed method called Kernel DM+V using several simulation and real-world experiments. The results of comparing the proposed time-dependent gas distribution modelling approaches to the time-independent version Kernel DM+V indicate a consistent improvement in the prediction of unseen measurements, particularly in dynamic scenarios under the condition that there is a sufficient spatial coverage. Dynamic scenarios are often defined as environments where strong fluctuations and gas plume development are present. For mobile robot olfaction, we are interested in sampling strategies that provide accurate gas distribution models given a small number of samples in a limited time span. Correspondingly, this thesis addresses the problem of selecting the most informative locations to acquire the next samples. As a further contribution, this thesis proposes a novel adaptive sensor planning method. This method is based on a modified artificial potential field, which selects the next sampling location based on the currently predicted gas distribution and the spatial distribution of previously collected samples. In particular, three objectives are used that direct the sensor towards areas of (1) high predictive mean and (2) high predictive variance, while (3) maximising the coverage area. The relative weight of these objectives corresponds to a trade-off between exploration and exploitation in the sampling strategy. This thesis discusses the weights or importance factors and evaluates the performance of the proposed sampling strategy. The results of the simulation experiments indicate an improved quality of the gas distribution models when using the proposed sensor planning method compared to commonly used methods, such as random sampling and sampling along a predefined sweeping trajectory. In this thesis, we show that applying a locality constraint on the proposed sampling method decreases the travelling distance, which makes the proposed sensor planning approach suitable for real-world applications where limited resources and time are available. As a real-world use-case, we applied the proposed sensor planning approach on a micro-drone in outdoor experiments. Finally, this thesis discusses the potential of using gas distribution modelling and sensor planning in large-scale outdoor real-world applications. We integrated the proposed methods in a framework for decision-making in hazardous inncidents where gas leakage is involved and applied the gas distribution modelling in two real-world use-cases. Our investigation indicates that the proposed sensor planning and gas distribution modelling approaches can be used to inform experts both about the gas plume and the distribution of gas in order to improve the assessment of an incident.
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Cowlard, Adam. "Sensor and model integration for the rapid prediction of concurrent flow flame spread." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/2753.
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Fire Safety Engineering is required at every stage in the life cycle of modern-day buildings. Fire safety design, detection and suppression, and emergency response are all vital components of Structural Fire Safety but are usually perceived as independent issues. Sensor deployment and exploitation is now common place in modern buildings for means such as temperature, air quality and security management. Despite the potential wealth of information these sensors could afford fire fighters, the design of sensor networks within buildings is entirely detached from procedures associated to emergency management. The experiences of Dalmarnock Fire Test Two showed that streams of raw data emerging from sensors lead to a rapid information overload and do little to improve the understanding of the complex phenomenon and likely future events during a real fire. Despite current sensor technology in other fields being far more advanced than that of fire, there is no justification for more complex and expensive sensors in this context. In isolation therefore, sensors are not sufficient to aid emergency response. Fire modelling follows a similar path. Two studies of Dalmarnock Fire Test One demonstrate clearly the current state of the art of fire modelling. A Priori studies by Rein et al. 2009 showed that blind prediction of the evolution of a compartment fire is currently beyond the state of the art of fire modelling practice. A Posteriori studies by Jahn et al. 2007 demonstrated that even with the provision of large quantities of sensor data, video footage, and prior knowledge of the fire; producing a CFD reconstruction was an incredibly difficult, laborious, intuitive and repetitive task. Fire fighting is therefore left as an isolated activity that does not benefit from sensor data or the potential of modelling the event. In isolation sensors and fire modelling are found lacking. Together though they appear to form the perfect compliment. Sensors provide a plethora of information which lacks interpretation. Models provide a method of interpretation but lack the necessary information to make this output robust. Thus a mechanism to achieve accurate, timely predictions by means of theoretical models steered by continuous calibration against sensor measurements is proposed. Issues of accuracy aside, these models demand heavy resources and computational time periods that are far greater than the time associated with the processes being simulated. To be of use to emergency responders, the output would need to be produced faster than the event itself with lead time to enable planning of an intervention strategy. Therefore in isolation, model output is not robust or fast enough to be implemented in an emergency response scenario. The concept of super-real time predictions steered by measurements is studied in the simple yet meaningful scenario of concurrent flow flame spread. Experiments have been conducted with PMMA slabs to feed sensor data into a simple analytical model. Numerous sensing techniques have been adapted to feed a simple algebraic expression from the literature linking flame spread, flame characteristics and pyrolysis evolution in order to model upward flame spread. The measurements are continuously fed to the computations so that projections of the flame spread velocity and flame characteristics can be established at each instant in time, ahead of the real flame. It was observed that as the input parameters in the analytical models were optimised to the scenario, rapid convergence between the evolving experiment and the predictions was attained.
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Akbar, Muhammad Sajjad. "Modelling, analysis and design of MAC and routing protocols for wireless body area sensor networks." Thesis, Bournemouth University, 2018. http://eprints.bournemouth.ac.uk/31049/.
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The main contribution of the thesis is to provide modeling, analysis, and design for Medium Access Control (MAC) and link-quality based routing protocols of Wireless Body Area Sensor Networks (WBASNs) for remote patient monitoring applications by considering saturated and un-saturated traffic scenarios. The design of these protocols has considered the stringent Quality of Service (QoS) requirements of patient monitoring systems. Moreover, the thesis also provides intelligent routing metrics for packet forwarding mechanisms while considering the integration of WBASNs with the Internet of Things (IoTs). First, we present the numerical modeling of the slotted Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) for the IEEE 802.15.4 and IEEE 802.15.6 standards. By using this modelling, we proposed a MAC layer mechanism called Delay, Reliability and Throughput (DRT) profile for the IEEE 802.15.4 and IEEE 802.15.6, which jointly optimize the QoS in terms of limited delay, reliability, efficient channel access and throughput by considering the requirements of patient monitoring system under different frequency bands including 420 MHz, 868 MHz and 2.4 GHz. Second, we proposed a duty-cycle based energy efficient adaptive MAC layer mechanism called Tele-Medicine Protocol (TMP) by considering the limited delay and reliability for patient monitoring systems. The proposed energy efficient protocol is designed by combining two optimizations methods: MAC layer parameter tuning and duty cycle-based optimization. The duty cycle is adjusted by using three factors: offered network traffic load, DRT profile and superframe duration. Third, a frame aggregation scheme called Aggregated-MAC Protocol Data Unit (A- MPDU) is proposed for the IEEE 802.15.4. A-MPDU provides high throughput and efficient channel access mechanism for periodic data transmission by considering the specified QoS requirements of the critical patient monitoring systems. To implement the scheme accurately, we developed a traffic pattern analysis to understand the requirements of the sensor nodes in patient monitoring systems. Later, we mapped the requirements on the existing MAC to find the performance gap. Fourth, empirical reliability assessment is done to validate the wireless channel characteristics of the low-power radios for successful deployment of WBASNs/IoTs based link quality routing protocols. A Test-bed is designed to perform the empirical experiments for the identification of the actual link quality estimation for different hospital environments. For evaluation of the test-bed, we considered parameters including Received Signal Strength Indicator (RSSI), Link Quality Indicator (LQI), packet reception and packet error rate. Finally, there is no standard under Internet Engineering Task Force (IETF) which provides the integration of the IEEE 802.15.6 with IPv6 networks so that WBASNs could become part of IoTs. For this, an IETF draft is proposed which highlights the problem statement and solution for this integration. The discussion is provided in Appendix B.
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Singh, Ranjit. "A novel design for a tactile sensor with mathematical modelling and data interpretation using neural networks." Thesis, Coventry University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283784.
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Hulhoven, Xavier. "Bioprocess software sensors development facing modelling and model uncertainties." Doctoral thesis, Universite Libre de Bruxelles, 2006. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210804.
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The exponential development of biotechnology has lead to a quasi unlimited number of potential products going from biopolymers to vaccines. Cell culture has therefore evolved from the simple cell growth outside its natural environment to its use to produce molecules that they do not naturally produce. This rapid development could not be continued without new control and supervising tools as well as a good process understanding. This requirement involves however a large diversity and a better accessibility of process measurements. In this framework, software sensors show numerous potentialities. The objective of a software sensor is indeed to provide an estimation of the system state variables and particularly those which are not obtained through in situ hardware sensors or laborious and expensive analysis. In this context, This work attempts to join the knowledge of increasing bioprocess complexity and diversity and the time scale of process developments and favours systematic modelling methodology, its flexibility and the speed of development. In the field of state observation, an important modelling constraint is the one induced by the selection of the state to estimate and the available measurements. Another important constraint is the model quality. The central axe of this work is to provide solutions in order to reduce the weight of these constraints to software sensors development. On this purpose, we propose four solutions to four main questions that may arise. The first two ones concern modelling uncertainties.1."How to develop a software sensor using measurements easily available on pilot scale bioreactor?" The proposed solution is a static software sensor using an artificial neural network. Following this modelling methodology we developed static software sensors for the biomass and ethanol concentrations in a pilot scale S. cerevisae cell culture using the measurement of titrating base quantity, agitation rate and CO&
Doctorat en sciences agronomiques et ingénierie biologique
info:eu-repo/semantics/nonPublished
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Michalaki, Paraskevi. "Estimation of a risk profile to operatives and the public from motorway hard-shoulder incursions." Thesis, Loughborough University, 2017. https://dspace.lboro.ac.uk/2134/33893.
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This project focuses on the risk to the operatives and the public arising from hard-shoulder incursions on motorways, which are defined as the temporary violation of this lane by a vehicle travelling on the nearside lane. Even though interest has been raised around safety when stopping on the hard-shoulder, there is no significant research conducted to investigate and quantify this risk. In this EngD project, motorway hard-shoulder accidents were investigated individually from the main traffic lanes to explore the factors affecting their severity and likelihood and identify potential differences using discrete choice and time-series modelling techniques. Based on the safety triangle theory, it was assumed that eliminating the contributory factors for injury accidents would also minimise the risk of hard-shoulder incursions, which were used as a risk indicator. An observation-based survey was conducted to gain initial knowledge on the frequency of incursions within a motorway stretch and also basic conditions that may affect the severity as well. Further to the survey, in order to collect hard-shoulder incursion data automatically, potential vehicle detection solutions were investigated. A radar sensor-based system was identified as the most suitable for this purpose and was adapted to suit the project s requirements. The sensor was installed on a motorway site, following a series of requirements to ensure safe and effective deployment. The data collected from the radar sensor were processed to minimise the errors and then corresponded to the traffic related and environmental data available for the same period of time. Using the Generalised Linear Autoregressive Moving Average model, the final models developed provided the factors that mostly affect the occurrence of hard-shoulder incursions. The main factors are temperature, humidity, traffic composition and average speed on the main carriageway. Using these models it is possible to quantify the risk and forecast when this will be minimised at a particular motorway section at any time. The risk is estimated according to the explanatory variables proposed, by inputting the predictions of these conditions in the model. This model is a tool that may then allow the operatives to be deployed on the network in the safest manner, according to the levels of tolerable risk.
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Patel, Manish R. "Modelling the ultraviolet environment at the surface of Mars and design of the Beagle 2 UV sensor." Thesis, Open University, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.396343.
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Ni, Houbo. "Realistic Modelling of Ultrasound Sensing for Autonomous Vehicles." Thesis, Linköpings universitet, Elektroniska Kretsar och System, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-162002.
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Ultrasonic sensors are popular in parking functions in automotive. They are used to measure distances between a car and obstacles near the car. Car companies need to prove that sensors are reliable before using them on vehicles since these sensors are safety-critical. Therefore, it has great practical value to research on the measurement and verification of ultrasonic sensors. The purpose of this thesis work is to analyse analog parts of some ultrasonic sensors. Measurement methods and three experimental setups are designed to get analog data. Ice, soil, stones or some other things on the road might cover the sensor, which limits the movement of horn and causes measurement errors. Sensor impedance is measured to check the possibility of blockage situation detection in a simulation of a real environment. The work also includes analysing the ultrasonic sensor beam pattern, the sound reflection from the environment, noise reduction, the relationship between the signal voltage amplitude and different positions of sensors, influences on different input signal lengths, and bandwidth investigation of the ultrasonic sensor. MATLAB compares measurement results with theory or simulation, All methods and setups are validated by getting measurement results successfully and correctly. Sensor blockage situation is recognized clearly by different impedance magnitudes. Sensors types under study are different from sensors installed on cars. However, other ultrasonic sensor measurements can utilize the same measurement methods and experimental setups. This thesis has been performed in collaboration with the company Volvo Car Corporation active safety department.
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Skoglar, Per. "Modelling and control of IR/EO-gimbal for UAV surveillance applications." Thesis, Linköping University, Department of Electrical Engineering, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1281.
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This thesis is a part of the SIREOS project at Swedish Defence Research Agency which aims at developing a sensor system consisting of infrared and video sensors and an integrated navigation system. The sensor system is placed in a camera gimbal and will be used on moving platforms, e.g. UAVs, for surveillance and reconnaissance. The gimbal is a device that makes it possible for the sensors to point in a desired direction.
In this thesis the sensor pointing problem is studied. The problem is analyzed and a system design is proposed. The major blocks in the system design are gimbal trajectory planning and gimbal motion control. In order to develop these blocks, kinematic and dynamic models are derived using techniques from robotics. The trajectory planner is based on the kinematic model and can handle problems with mechanical constraints, kinematic singularity, sensor placement offset and reference signal transformation.
The gimbal motion controller is tested with two different control strategies, PID and LQ. The challenge is to perform control that responds quickly, but do not excite the damping flexibility too much. The LQ-controller uses a linearization of the dynamic model to fulfil these requirements.