Дисертації з теми "Surveillance signal processing"
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Adams, Andrew J. "Multispectral persistent surveillance /." Online version of thesis, 2008. http://hdl.handle.net/1850/7070.
Повний текст джерелаGórski, Tomasz. "Space-time adaptive signal processing for sea surveillance on-shore stationary radars." Télécom Bretagne, 2008. http://www.theses.fr/2008TELB0075.
Повний текст джерелаWortham, Cody. "Space-Time Processing for Ground Surveillance Radar." Thesis, Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/14468.
Повний текст джерелаHallermeyer, Alexandre. "Traitement du Signal d’un LIDAR Doppler scannant dédié à la surveillance aéroportuaire." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLC007/document.
Повний текст джерелаAn algorithm was developed to estimate precisely wake vortices parameters (positions and circulations) using spectral data provided by a LIDAR. It is articulated in 3 main stages: The first one allows to detect the presence of vortices and to make a rough localization thanks to the method of the velocity envelopes. The second step is to refine the estimation of vortex positions using an optimization of the least squares criterion. This step also permits to make an first estimation of the vortices circulation. The third and final step focuses on estimating vortex circulations by maximizing the likelihood criterion. Estimates are becoming finer and more focused on the most critical parameters. The development of this algorithm required the use of several models (LIDAR, wake vortices, atmosphere) and to formulate a number of simplifying assumptions in order to reach a reasonable computational cost. The proposed algorithm was then subjected to a performance evaluation, the interest being focused on the robustness with respect to the different noises altering the measurement, particularly the one related to the atmospheric turbulence, and with respect to the model errors. This evaluation was carried out both on simulated data using simplified parametric models, and on Large Eddy Simulations.The instrumental parameters of LIDAR are potential degrees of freedom to improve the performance of the estimator, in particular for the most critical quantities, that is to say the circulation values. The calculation of the performance of the estimator requiring a significant computational cost, it lends itself poorly for optimization purposes. This is why a study of the influence of the LIDAR parameters on the Cramér-Rao Bound (CRB) was carried out. This study allowed to understand the influence of the instrumental parameters and to reach an optimal configuration for the CRB
Comstedt, Erik. "Effect of additional compression features on h.264 surveillance video." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-30901.
Повний текст джерелаSekak, Fatima. "Microwave radar techniques and dedicated signal processing for Vital Signs measurement." Thesis, Université de Lille (2018-2021), 2021. https://pepite-depot.univ-lille.fr/LIBRE/EDENGSYS/2021/2021LILUN033.pdf.
Повний текст джерелаIn the context of securing transportation systems, short-range monitoring of people's activity, in particular the driver's activity in a vehicle, is a major issue in the improvement of the driver assistance system. The application targeted in this work concerns mainly the railway domain.Respiratory and heart rates of the driver are key indicators for the evaluation of the physiological state. Conventional methods of measuring these vital signs rely on sensors operating in direct contact with the skin. Therefore, the intrusive character of these solutions is not suited for the transportation domain, especially because of the induced discomfort. In this work, a microwave radar solution operating at low power is proposed for the continuous measurement of respiratory and cardiac activity signals. In particular, physiological signals (heartbeat, mechanical movement of the rib cage) are indicators of human activity that can be detected at a distance (up to ten meters) using radiated microwave electromagnetic waves.Although the literature shows a growing interest in the development of radar techniques dedicated to the surveillance of people, there is no robust, sensitive and accurate commercial device available to date. A detailed analysis of the electrical and geometrical parameters of the radar technique is proposed in this work in order to identify the sources of uncertainties, to define the optimal parameters, to validate experimentally the proposed solution. An original signal processing, based on the cyclostationary approach, is implemented in order to extract the parameters of interest in reference or disturbed measurement environments. The proposed hardware solutions associated with an optimal signal processing allow to foresee radar architectures adapted to non-laboratory contingencies
Nyström, Axel. "Evaluation of Multiple Object Tracking in Surveillance Video." Thesis, Linköpings universitet, Datorseende, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666.
Повний текст джерелаFirla, Marcin. "Automatic signal processing for wind turbine condition monitoring. Time-frequency cropping, kinematic association, and all-sideband demodulation." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAT006/document.
Повний текст джерелаThis thesis proposes a three signal-processing methods oriented towards the condition monitoring and diagnosis. In particular the proposed techniques are suited for vibration-based condition monitoring of rotating machinery which works under highly non-stationary operational condition as wind turbines, but it is not limited to such a usage. All the proposed methods are automatic and data-driven algorithms.The first proposed technique enables a selection of the most stationary part of signal by cropping time-frequency representation of the signal.The second method is an algorithm for association of spectral patterns, harmonics and sidebands series, with characteristic frequencies arising from kinematic of a system under inspection. This method features in a unique approach dedicated for rolling-element bearing which enables to overcome difficulties caused by a slippage phenomenon.The third technique is an all-sideband demodulation algorithm. It features in a multi-rate filter and proposes health indicators to facilitate an evaluation of the condition of the investigated system.In this thesis the proposed methods are validated on both, simulated and real-world signals. The presented results show good performance of all the methods
Song, Bi. "Scene analysis, control and communication in distributed camera networks." Diss., [Riverside, Calif.] : University of California, Riverside, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3359910.
Повний текст джерелаIncludes abstract. Title from first page of PDF file (viewed January 27, 2010). Includes bibliographical references (p. 99-105). Issued in print and online. Available via ProQuest Digital Dissertations.
Kazemisaber, Mohammadreza. "Clutter Removal in Single Radar Sensor Reflection Data via Digital Signal Processing." Thesis, Linnéuniversitetet, Institutionen för fysik och elektroteknik (IFE), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-99874.
Повний текст джерелаAbou, Ghaida Hussein. "Modélisation de l’équilibre et système de surveillance posturale." Thesis, Rennes 1, 2014. http://www.theses.fr/2014REN1S167.
Повний текст джерелаProblems of balance are often diagnosed thanks to plantar pressure cartography systems or forces platform that measure the center of pressure displacement. These professional systems are restricted in use to medical environments, and until now, the balance monitoring systems do not offer complete satisfaction in terms of mobility and acceptability. In order to overcome these limitation and in the context of telemedicine and e-health, we aimed to develop tools for ambulatory monitoring of postural equilibrium and to understand the balance control. We have first undertaken a theoretical study on the feasibility of measuring plantar pressure and dynamic displacement of the center of pressure, from a very small number of sensors. For these applications, we have proposed a simplified mechanical foot model, as well as related assumptions. The model describes the physical relationship between foot posture and distribution of plantar pressures following its biomechanical characteristics. Based on a prototype of an instrumented insole with only 3 sensors, we have verified experimentally the ability of the system and the methods to generate both the stabilogram and the plantar pressure maps. Comparison is made with a matrix reference system, and characterization in terms of uncertainty in the case of normal foot in standing position and during walking is detailed. The measured stabilogram can be analyzed to characterize the signature of balance. We have also proposed a specific three-dimensional model describing the dynamics of balance. Based on simulation, it leads to identify the main physiological parameters related to balance control
Bechar, Hassane. "Comparaison d'images : Application à la surveillance et au suivi de trajectoire." Nancy 1, 1987. http://www.theses.fr/1987NAN10062.
Повний текст джерелаLecomte, Sébastien. "Classification partiellement supervisée par SVM : application à la détection d’événements en surveillance audio." Thesis, Troyes, 2013. http://www.theses.fr/2013TROY0031/document.
Повний текст джерелаThis thesis addresses partially supervised Support Vector Machines for novelty detection (One-Class SVM). These have been studied to design abnormal audio events detection for supervision of public infrastructures, in particular public transportation systems. In this context, the null hypothesis (“normal” audio signals) is relatively well known (even though corresponding signals can be notably non stationary). Conversely, every “abnormal” signal should be detected and, if possible, clustered with similar signals. Thus, a reference system based on a single model of normal signals is presented, then we propose to use several concurrent One-Class SVM to cluster new data. Regarding the amount of data to process, special solvers have been studied. The proposed algorithms must be real time. This is the reason why we have also investigated algorithms with warm start capabilities. By the study of these algorithms, we have proposed a unified framework for One Class and Binary SVMs, with and without bias. The proposed approach has been validated on a database of real signals. The whole process applied to the monitoring of a subway station has been presented during the final review of the European Project VANAHEIM
Trachi, Youness. "On induction machine faults detection using advanced parametric signal processing techniques." Thesis, Brest, 2017. http://www.theses.fr/2017BRES0103/document.
Повний текст джерелаThis Ph.D. thesis aims to develop reliable and cost-effective condition monitoring and faults detection architectures for induction machines. These architectures are mainly based on advanced parametric signal processing techniques. To analyze and detect faults, a parametric stator current model under stationary conditions has been considered. It is assumed to be multiple sinusoids with unknown parameters in noise. This model has been estimated using parametric techniques such as subspace spectral estimators and maximum likelihood estimator. A fault severity criterion based on the estimation of the stator current frequency component amplitudes has also been proposed to determine the induction machine failure level. A novel faults detector based on hypothesis testing has been also proposed. This detector is mainly based on the generalized likelihood ratio test detector with unknown signal and noise parameters. The proposed parametric techniques have been evaluated using experimental stator current signals issued from induction machines under two considered faults: bearing and broken rotor bars faults.Experimental results show the effectiveness and the detection ability of the proposed parametric techniques
Oubrahim, Zakarya. "On electric grid power quality monitoring using parametric signal processing techniques." Thesis, Brest, 2017. http://www.theses.fr/2017BRES0102/document.
Повний текст джерелаThis thesis deals with electric grid monitoring of power quality (PQ) disturbances using parametric signal processing techniques. The first contribution is devoted to the parametric spectral estimation approach for signal parameter extraction. The proposed approach exploits the multidimensional nature of the electrical signals.For spectral estimation, it uses an optimization algorithm to minimize the likelihood function. In particular, this algorithm allows to improve the estimation accuracy and has lower computational complexity than classical algorithms. An in-depth analysis of the proposed estimator has been performed. Specifically, the estimator performances are evaluated under noisy, harmonic, interharmonic, and off-nominal frequency environment. These performances are also compared with the requirements of the IEEE Standard C37.118.2011. The achieved results have shown that the proposed approach is an attractive choice for PQ measurement devices such as phasor measurement units (PMUs). The second contribution deals with the classification of power quality disturbances in three-phase power systems. Specifically, this approach focuses on voltage sag and swell signatures. The proposed classification approach is based on two main steps: 1) the signal pre-classification into one of 4 pre-classes and 2) the signature type classification using the estimate of the symmetrical components. The classifier performances have been evaluated for different data length, signal to noise ratio, interharmonic, and total harmonic distortion. The proposed estimator and classifier are validated using real power system data obtained from the DOE/EPRI National Database of Power System Events. The achieved simulations and experimental results clearly illustrate the effectiveness of the proposed techniques for PQ monitoring purpose
Bonnieux, Sébastien. "Flotteur pour la surveillance pluridisciplinaire de l’environnement marin. De l’expertise métier aux codes embarqués." Thesis, Université Côte d'Azur, 2020. http://www.theses.fr/2020COAZ4072.
Повний текст джерелаAs part of an ERC (European Research Council) project conducted at Geoazur from 2009 to 2015 by Guust Nolet, an autonomous profiler float equipped with a hydrophone and able to carry up to 8 sensors has been developed. It aims to acquire data in oceanic areas, poorly covered by current instrumentation. However, these data are necessary to carry out studies in various scientific fields, for example, to study the internal structure of the earth in geosciences (via the recording of seismic waves propagating inside the earth), the thermal balance of oceans in climatology, or the distribution of marine mammals in the oceans in biology. Most data must be processed before being transmitted by satellite because of the very limited transmission bandwidth. Data processing applications are usually developed by embedded systems specialists who have a good knowledge of the characteristics specific to the instrument. However, the need to involve these specialists greatly limits the flexibility, or even the ability of scientists to adapt the applications to their needs.In order to enable scientists to write applications for the instrument, we have created the MeLa (Mermaid Language) programming language, specifically designed for the Mermaid float. The language makes it possible to hide embedded systems specific aspects. It is based on computer models that allow computing the resources usage of the instrument (i.e., processor, power, satellite transmission) in order to ensure that the instrument limits are not exceeded. Models are also used to compose (i.e., combine) several applications to be installed on the same instrument and to ensure that they are compatible. Finally, models are used to generate reliable and efficient code (i.e., without bugs and efficient), on the one hand, to simulate applications on a personal computer and verify their behavior, and, on the other hand, to generate the embedded code used to program the instruments.This thesis is organized into four chapters. In the first chapter, we start by presenting the scientific and social issues involved in the acquisition of data in the oceans, then we introduce the Mermaid float and how it can respond to these issues and end by presenting different programming approaches for this type of instrument. The second chapter corresponds to an article published in the OCEANS 2019 conference proceedings. It shows the technical aspects of the MeLa language and in particular how we use models and how the approach is validated on an Arduino development board. The third chapter corresponds to an article published in the Sensors journal and is more focused on the use of language, a development method is proposed, and two applications are developed for the detection of earthquakes and the detection of blue whales. In the final chapter, we summarize the conclusions and offer a perspective of future developments
Anghel, Andrei. "Analyse temps-frequence et traitement des signaux RSO à haute résolution spatiale pour la surveillance des grands ouvrages d'art." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAT107/document.
Повний текст джерелаThe thesis is composed of two research axis. The first one consists in proposing time-frequency signal processing tools for frequency modulated continuous wave (FMCW) radars used for displacements measurements, while the second one consists in designing a spaceborne synthetic aperture radar (SAR) signal processing methodology for infrastructure monitoring when an external point cloud of the envisaged structure is available. In the first part of the thesis, we propose our solutions to the nonlinearity problem of an X-band FMCW radar designed for millimetric displacement measurements of short-range targets. The nonlinear tuning curve of the voltage controlled oscillator from the transceiver can cause a dramatic resolution degradation for wideband sweeps. To mitigate this shortcoming, we have developed two time warping-based methods adapted to wideband nonlinearities: one estimates the nonlinear terms using the high order ambiguity function, while the other is an autofocus approach which exploits the spectral concentration of the beat signal. Onwards, as the core of the thesis, we propose a novel method for scattering centers detection and tracking in spaceborne SAR images adapted to infrastructure monitoring applications. The method is based on refocusing each SAR image on a provided 3D point cloud of the envisaged infrastructure and identifying the reliable scatterers to be monitored by means of four dimensional (4D) tomography. The refocusing algorithm is compatible with stripmap, spotlight and sliding spotlight SAR images and consists of an azimuth defocusing followed by a modified back-projection algorithm on the given set of points which exploits the time-frequency structure of the defocused azimuth signal. The scattering centers of the refocused image are detected in the 4D tomography framework by testing if the main response is at zero elevation in the local elevation-velocity spectral distribution. The mean displacement velocity is estimated from the peak response on the zero elevation axis, while the displacements time series for detected single scatterers is computed as double phase difference of complex amplitudes.Finally, we present the measurement campaigns carried out on the Puylaurent water-dam and the Chastel landslide using GPS measurements, topographic surveys and laser scans to generate the point clouds of the two structures. The comparison between in-situ data and the results obtained by combining TerraSAR-X data with the generated point clouds validate the developed SAR signal processing chain
Teza cuprinde două axe principale de cercetare. Prima axă abordează aspecte metodologice de prelucraretimp-frecvenţă a semnalelor furnizate de radare cu emisie continuă şi modulaţie de frecvenţă (FMCW)în contextul măsurării deplasărilor milimetrice. În cadrul celei de-a doua axe, este proiectată şi validatăo metodă de prelucrare a imaginilor satelitare SAR (radar cu apertură sintetică) ce este destinatămonitorizării infrastructurii critice şi care se bazează pe existenţa unui model 3D al structurii respective.În prima parte a tezei, sunt investigate soluţii de corecţie a neliniarităţii unui radar FMCW în bandaX destinat măsurării deplasărilor milimetrice. Caracteristica de comandă neliniară a oscilatorului debandă largă determină o degradare a rezoluţiei în distanţă. Pentru a rezolva acest inconvenient, au fostelaborate două metode de corecţie a neliniarităţii, adaptate pentru semnale de bandă largă, ce se bazeazăpe conceptul de reeşantionare neuniformă sau deformare a axei temporare. Prima abordare estimeazăparametrii neliniarităţii utilizând funcţii de ambiguitate de ordin superior, iar cea de-a doua exploateazăo măsură de concentraţie spectrală a semnalului de bătăi într-un algoritm de autofocalizare în distanţă.În a doua parte a lucrării, este propusă o metodologie generală de detecţie şi monitorizare a centrilorde împrăştiere în imagini SAR în scopul monitorizării elementelor de infrastructură critică. Metoda sebazează pe refocalizarea fiecărei imagini radar pe un model 3D al structurii investigate în scopul identificăriicentrilor de împrăştiere pertinenţi (ţinte fiabile ce pot fi monitorizate în timp) cu ajutorul tomografiei SAR4D (distanţă-azimut-elevaţie-viteză de deplasare). Algoritmul de refocalizare este compatibil cu imaginiSAR achiziţionate în moduri diferite (« stripmap », « spotlight » şi « sliding spotlight ») şi constă într-odefocalizare în azimut urmată de o retroproiecţie modificată (condiţionată de structura timp-frecvenţă asemnalului) pe modelul 3D al structurii. Ţintele sunt identificate în stiva de imagini refocalizate cu ajutorultomografiei 4D prin efectuarea unui test de conformitate cu ipoteza că centrii de împrăştiere pertinenţivor avea elevaţie zero în planul local elevaţie-viteză. Viteza medie de deformare corespunde maximuluide pe axa de elevaţie nulă, iar seria temporară a deplasărilor se obţine printr-o dublă diferenţă de fază aamplitudinilor complexe corespunzătoare ţintelor identificate.În final sunt prezentate campaniile de măsurători pe teren efectuate la un baraj şi o alunecare de terendin regiunea Puylaurent (Franţa) destinate obţinerii modelului 3D al celor două elemente de infrastructurăprin măsurători GPS, topografice şi LIDAR. Comparaţia între deformările măsurate pe teren şi rezultateleobţinute prin combinarea imaginilor SAR cu modelele 3D au permis validarea metodologiei propuse
Ghadban, Nisrine. "Fusion de l'information dans les réseaux de capteurs : application à la surveillance de phénomènes physiques." Thesis, Troyes, 2015. http://www.theses.fr/2015TROY0037/document.
Повний текст джерелаThis thesis investigates two major problems that are challenging the wireless sensor networks (WSN): the measurements accuracy in the regions with a low density of sensors and the growing volume of data collected by the sensors. The first contribution of this thesis is to enhance the collected measurements accuracy, and hence to strengthen the monitored space coverage by the WSN, by means of the sensors mobility strategy. To this end, we address the estimation problem in a WSN by kernel-based machine learning methods, in order to model some physical phenomenon, such as a gas diffusion. We propose several optimization schemes to increase the relevance of the model. We take advantage of the sensors mobility to introduce several mobility scenarios. Those scenarios define the training set of the model and the sensor that is selected to perform mobility based on several mobility criteria. The second contribution of this thesis addresses the dimensionality reduction of the set of collected data by the WSN. This dimensionality reduction is based on the principal component analysis techniques. For this purpose, we propose several strategies adapted to the restrictions in WSN. We also study two well-known problems in wireless networks: the non-synchronization problem between nodes of the network, and the noise in measures and communication. We propose appropriate solutions with Gossip-like algorithms and smoothing mechanisms. All the techniques developed in this thesis are validated in a WSN dedicated to the monitoring of a physical species leakage such as the diffusion of a gas
Lastapis, Mathieu. "Surveillance de la santé des structures aéronautiques en composites : développement d'un système embarqué à base d'accéléromètres." Thesis, Toulouse, INSA, 2011. http://www.theses.fr/2011ISAT0021.
Повний текст джерелаThe structural health monitoring, or SHM, represents today a key challenge today, with a massive use of composites in the field of transport. This material, lighter than a conventional alloy, is very attractive for airplanes, trains, boats or cars manufacturing. This allows significant energy savings, but can hide internal defects invisible from the outside. At this point, dedicated supervision is essential. Blades of turboprop plane (A400M, ATR, etc.) are in face of the same problems. Determination of structural defects by the use of sensors is the key solution for the research in this field. Thus, this problem has two solutions: studying blade performances and designing an embedded system able to record data and/or monitoring the structural health. The research studies presented in this thesis represent the first results of damaged blade performances. It leads to the design of a first embedded data recorder of blade parameters and computes a first dedicated algorithm for monitoring the blade structural health and damaging events (shocks, over-speeds, over-vibrations)
Cédric, Peeters. "Advanced signal processing for the identification and diagnosis of the condition of rotating machinery." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI107.
Повний текст джерелаThis Ph.D. dissertation targets innovative methods for vibration-based condition monitoring of rotating machinery. Substantial benefits can be achieved from an economical and a safety point of view using condition monitoring. One of the most popular methods to gather information about the state of machine parts is through the analysis of machine vibrations. Most of these vibrations are directly linked to periodical behavior of subsystems within the machine like e.g. rotating shafts, gears, rotating electrical fields, etc. This knowledge can be exploited to enable faultdependent processing schemes. This dissertation investigates how to implement and utilize these processing schemes and details the steps in such a procedure. Typically, the first prerequisite for advanced analysis is the availability of the instantaneous rotation speed. This speed needs to be known since most frequency-based analysis techniques assume stationary behavior. Knowledge of the speed thus allows for compensating speed fluctuations, for example through angular resampling of the vibration signal. While there are hardware-based solutions for speed estimation using angle encoders or tachometers, this thesis investigates the potential in vibration signals for speed estimation. After speed estimation and angular resampling, a common next step is to separate the signal into deterministic and stochastic components. The cepstrum editing procedure is examined for its efficacy and applicability. Afterwards, different filtering methods are inspected as to improve the signal-to-noise ratio of the signal content of interest. Existing methods using conventional criteria are investigated together with a novel blind filtering methodology. The final step in the multi-step processing scheme is to search for the potential fault. Statistical indicators can be calculated on the processed time domain signal and tracked over time to check for increases. In many cases, the fault signature exhibits cyclostationary behavior. Therefore this dissertation also examines different cyclostationary analysis techniques. Lastly, the performance of the different processing methods is validated on two experimental vibration data sets of wind turbine gearboxes
Sabor, Jalal. "Processeur de signal digital à architecture parallèle implémenté en FPGA. Application à un système de surveillance à domicile des nourrissons à risque de MSN." Rouen, 1995. http://www.theses.fr/1995ROUE5019.
Повний текст джерелаPannetier, Benjamin. "Fusion de données pour la surveillance du champ de bataille." Phd thesis, Université Joseph Fourier (Grenoble), 2006. http://tel.archives-ouvertes.fr/tel-00377247.
Повний текст джерелаCathelain, Guillaume. "Ballistocardiographie et applications." Thesis, Université Paris sciences et lettres, 2020. http://www.theses.fr/2020UPSLP029.
Повний текст джерелаGlobally, healthcare systems have increasing costs and the number of hospitalizations grows. Telehealth brings hospital at home and provides health structures with new opportunities to improve the patient care pathway. Physiological monitoring is a prerequisite in efficient telehealth systems and is performed by connected medical devices that are not fully automated. Patients need to use them actively on a day-to-day basis: these drawbacks lead either to patient disengagement or to additional caregiver support. Passive contactless vital signs’ monitors, such as ballistocardiograms sleep trackers that measure motor, respiratory and cardiac activities, can solve the telehealth inefficiency. Moreover, they are more comfortable and safer for patients than traditional monitors, which is crucial for neonatal neurological development or in case of mental degeneration, though they are currently less accurate. How to improve physiological monitoring accuracy in ballistocardiography to increase telehealth efficiency? In this thesis, materials are provided by a self-designed accelerometer-based instrumentation, a dedicated software, a heartbeat simulator, and measurement campaigns for raw ballistocardiograms’ databases. Novel analog amplification and digital filtering methods are investigated to improve ballistocardiography accuracy. The ballistocardiographic force, coming from the aortic arch deformation during the ventricular systole and measured on the bedside, is indeed modulated by respiratory and motor activities, and is polluted by environment mechanical artifacts. Furthermore, the ballistocardiography is unstandardized and ballistocardiograms have high inter- and intra-variabilities, depending on the beddings, the position in bed, the morphology and the physiology of the patient. Analog amplification is studied from two perspectives: the mechanical amplification of ballistocardiograms from the patient to the sensor, and the electronic amplification of the analog acceleration signal. First, concerning the mechanical amplification, a novel waveguide bedding, a cotton tape encircling the mattress, was invented to concentrate the strain energy of the ballistocardiographic force in one direction, from the thorax straight to the attached sensor. Second, concerning the electronic amplification, a mixed-signal front-end was conceived to optimize the tradeoff between the electronic amplifier gain and the saturation time after a movement. The conditioning circuit measures the unamplified sensor output, passes it through a digital filter with a sharp transition frequency bandwidth and a proper initialization, and analogically amplifies the difference between this unwanted synthesized signal and the unamplified sensor output using a low noise instrumentation amplifier. Digital filtering methods aims at separating signal sources, removing artifacts then detecting vital signs. Three original algorithms have been designed to efficiently recognize heartbeats in ballistocardiograms. The first algorithm is dynamic time warping template matching, where a heartbeat template is used to match heartbeats using a warping distance. The second algorithm models ballistocardiograms with periodic hidden Markov models. The third algorithm, the U-Net neural network, is supervised and segments heartbeats in ballistocardiograms. Finally, ballistocardiograms are mechanically and electronically amplified by 12 dB and 21 dB respectively, without saturation time; and digital filtering algorithms reach a 97% precision and 96% recall for heartbeats detection. Shortly, the designed ballistocardiograph will be clinically evaluated in a pediatric intensive care unit and in telemedicine against other ballistocardiographs and the gold standard methods
Church, Donald Glen. "Reducing Error Rates in Intelligence, Surveillance, and Reconnaissance (ISR) Anomaly Detection via Information Presentation Optimization." Wright State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=wright1452858183.
Повний текст джерелаLi, Zhongyang. "Modélisation de signaux longs multicomposantes modulés non linéairement en fréquence et en amplitude : suivi de ces composantes dans le plan temps-fréquence." Thesis, Grenoble, 2013. http://www.theses.fr/2013GRENT026/document.
Повний текст джерелаIn this thesis, a novel method is proposed for modeling the non-linear amplitude and frequency modulations of non-stationary multi-component signals of long duration. The method relies on the decomposition of the signal into short time segments to carry out local modelings on these segments. In order to initialize the modeling, a first step is designed which can be considered as an independent estimator of the modulations over the entire duration of the signal. The originality of this approach lies in the definition of the total divergence matrix integrating simultaneously the amplitude and frequency values, which are employed for the association of a peak to a component according to a stochastic acceptation criteria. Following the initialization, the proposed method estimates the modulations by the step sequence of segmentation, modeling and fusion. The locally obtained modulation functions estimated by maximum likelihood are finally connected in the fusion step which suppresses their discontinuity and yields the global estimation over the entire signal duration. All these steps are defined in order to be able to model multicomponent signals with births and deaths, making one of its original features compared to existing techniques. The results on real and simulated signals have shown the good performance and adaptability of the proposed method
Arnold-Bos, Andreas. "La surveillance maritime en imagerie radar bistatique : théorie, simulation, contribution à la détection automatique du sillage des navires." Phd thesis, Université de Bretagne occidentale - Brest, 2010. http://tel.archives-ouvertes.fr/tel-00763477.
Повний текст джерелаXu, Jingxin. "Unusual event detection in crowded scenes." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/76365/1/Jingxin_Xu_Thesis.pdf.
Повний текст джерелаAl, Nazer Rouba. "Système de mesure d'impédance électrique embarqué, application aux batteries Li-ion." Phd thesis, Université de Grenoble, 2014. http://tel.archives-ouvertes.fr/tel-00958783.
Повний текст джерелаDaumont, Steredenn. "Techniques de démodulation aveugle en interception de signaux MIMO." Phd thesis, Université Rennes 1, 2009. http://tel.archives-ouvertes.fr/tel-00441830.
Повний текст джерелаBonnel, Julien. "Analyse de la dispersion acoustique UBF (0-150 Hz) pour la surveillance et la caractérisation du milieu marin." Phd thesis, Grenoble INPG, 2010. http://tel.archives-ouvertes.fr/tel-00522789.
Повний текст джерелаLe, Borgne Yann-Aël. "Learning in wireless sensor networks for energy-efficient environmental monitoring." Doctoral thesis, Universite Libre de Bruxelles, 2009. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210334.
Повний текст джерелаIn environmental monitoring studies, many applications are expected to run unattended for months or years. Sensor nodes are however constrained by limited resources, particularly in terms of energy. Since communication is one order of magnitude more energy-consuming than processing, the design of data collection schemes that limit the amount of transmitted data is therefore recognized as a central issue for wireless sensor networks.
An efficient way to address this challenge is to approximate, by means of mathematical models, the evolution of the measurements taken by sensors over space and/or time. Indeed, whenever a mathematical model may be used in place of the true measurements, significant gains in communications may be obtained by only transmitting the parameters of the model instead of the set of real measurements. Since in most cases there is little or no a priori information about the variations taken by sensor measurements, the models must be identified in an automated manner. This calls for the use of machine learning techniques, which allow to model the variations of future measurements on the basis of past measurements.
This thesis brings two main contributions to the use of learning techniques in a sensor network. First, we propose an approach which combines time series prediction and model selection for reducing the amount of communication. The rationale of this approach, called adaptive model selection, is to let the sensors determine in an automated manner a prediction model that does not only fits their measurements, but that also reduces the amount of transmitted data.
The second main contribution is the design of a distributed approach for modeling sensed data, based on the principal component analysis (PCA). The proposed method allows to transform along a routing tree the measurements taken in such a way that (i) most of the variability in the measurements is retained, and (ii) the network load sustained by sensor nodes is reduced and more evenly distributed, which in turn extends the overall network lifetime. The framework can be seen as a truly distributed approach for the principal component analysis, and finds applications not only for approximated data collection tasks, but also for event detection or recognition tasks.
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Les réseaux de capteurs sans fil forment une nouvelle famille de systèmes informatiques permettant d'observer le monde avec une résolution sans précédent. En particulier, ces systèmes promettent de révolutionner le domaine de l'étude environnementale. Un tel réseau est composé d'un ensemble de capteurs sans fil, ou unités sensorielles, capables de collecter, traiter, et transmettre de l'information. Grâce aux avancées dans les domaines de la microélectronique et des technologies sans fil, ces systèmes sont à la fois peu volumineux et peu coûteux. Ceci permet leurs deploiements dans différents types d'environnements, afin d'observer l'évolution dans le temps et l'espace de quantités physiques telles que la température, l'humidité, la lumière ou le son.
Dans le domaine de l'étude environnementale, les systèmes de prise de mesures doivent souvent fonctionner de manière autonome pendant plusieurs mois ou plusieurs années. Les capteurs sans fil ont cependant des ressources limitées, particulièrement en terme d'énergie. Les communications radios étant d'un ordre de grandeur plus coûteuses en énergie que l'utilisation du processeur, la conception de méthodes de collecte de données limitant la transmission de données est devenue l'un des principaux défis soulevés par cette technologie.
Ce défi peut être abordé de manière efficace par l'utilisation de modèles mathématiques modélisant l'évolution spatiotemporelle des mesures prises par les capteurs. En effet, si un tel modèle peut être utilisé à la place des mesures, d'importants gains en communications peuvent être obtenus en utilisant les paramètres du modèle comme substitut des mesures. Cependant, dans la majorité des cas, peu ou aucune information sur la nature des mesures prises par les capteurs ne sont disponibles, et donc aucun modèle ne peut être a priori défini. Dans ces cas, les techniques issues du domaine de l'apprentissage machine sont particulièrement appropriées. Ces techniques ont pour but de créer ces modèles de façon autonome, en anticipant les mesures à venir sur la base des mesures passées.
Dans cette thèse, deux contributions sont principalement apportées permettant l'applica-tion de techniques d'apprentissage machine dans le domaine des réseaux de capteurs sans fil. Premièrement, nous proposons une approche qui combine la prédiction de série temporelle avec la sélection de modèles afin de réduire la communication. La logique de cette approche, appelée sélection de modèle adaptive, est de permettre aux unités sensorielles de determiner de manière autonome un modèle de prédiction qui anticipe correctement leurs mesures, tout en réduisant l'utilisation de leur radio.
Deuxièmement, nous avons conçu une méthode permettant de modéliser de façon distribuée les mesures collectées, qui se base sur l'analyse en composantes principales (ACP). La méthode permet de transformer les mesures le long d'un arbre de routage, de façon à ce que (i) la majeure partie des variations dans les mesures des capteurs soient conservées, et (ii) la charge réseau soit réduite et mieux distribuée, ce qui permet d'augmenter également la durée de vie du réseau. L'approche proposée permet de véritablement distribuer l'ACP, et peut être utilisée pour des applications impliquant la collecte de données, mais également pour la détection ou la classification d'événements.
Doctorat en Sciences
info:eu-repo/semantics/nonPublished
Gousseau, William. "Pronostic de dégradation d'endommagements de roulements sur application aéronautique par analyse vibratoire." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSEI063.
Повний текст джерелаAs part of preventive maintenance of its engines, Safran Aircraft Engines wishes to complete its diagnostic operations with a reliable prognosis of the residual life of the bearings. Following an attack, there is currently a great deal of uncertainty about the remaining life before bearing failure from the threshold of vibrational observability of the damage. Current algorithms diagnose an approximate stage of degradation and generate alarm messages of different levels, each level corresponding to a different stage of degradation, combining confidence and severity of diagnosis. An important aspect of the prognosis is the taking into account of the contextual parameters influencing the rate of degradation. The objectives of this thesis are to have methods and tools to quantify a running time remaining before bearing failure with regard to: - the severity of the damage detected, - the environmental conditions of operation, - the depth The industrial constraints associated with these objectives are as follows: 1) The prognosis should be based, at least, on high-frequency vibratory measurements of a few kHz (accelerometers), contextual data (the rotational speeds of the different rotors, for example, or the amplitudes of the levels piloted on them), rotation regimes, revealing a loading of the bearings) 2). Constituing a database of tests resulting from a plan of experiments: these tests will have to take into account the constraints related to the control of the parameters considered to be significantly influential 3) This database must take into account the representativity of the vibratory environment of an aircraft engine. 4) Propose a tool or method of prognosis taking into account the nature of the bearing to consider
Guigue, Lisa. "Evaluation clinique de la pression artérielle centrale à partir de la mesure par cathétérisme radial en utilisant la modélisation de l'arbre artériel, de la liaison hydraulique et du capteur. Intégration de la fonction dans un dispositif de surveillance de la qualité de la mesure de la pression artérielle." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAS036.
Повний текст джерелаAortic pressure is generally recognized as a good index of the hemodynamic state of a patient. In intensive care units, aortic pressure is indirectly estimated via a radial catheter-tansducer system. The present study aims to remove the obstacles to a reliable evaluation of central pressure via the radial catheter-transducer system commonly used in clinics. These obstacles can be due to :1.technical problems occurring between the radial catheter and the sensor;}2.pathophysiological problems affecting the arterial tree between the heart and peripheral arteries. Several clinical situations have been identified in which alterations of the physical properties of the vasculature do not allow a reliable estimation of central arterial pressure using the common radial setting. One of these phenomena is the so called central-to-radial arterial pressure gradient.CATARSI, a medical device developped by AII SAS, affords a solution to the first group of problems by providing an index of the quality of the signal provided by the radial catheter-transducer system.Under pathophysiological conditions affecting the arterial vascualture of the patient, early detection of a mismatch between peripheral and central arterial pressure would also be of great clinical value. In this view, a new functionality could be develop to implement CATARSI. However, to achieve this goal, it is first necessary to understand, evaluate and modelize the precise pathophysiological mechanisms involved in these particular situations.The study contains three steps :1.Experimental evaluation, by oscillometry and catheterization, of AP propagation-time on the human arterial tree (aortic, radial, femoral arterial pressure) during a central-to-radial arterial pressure gradient. This evaluation has been carried out on patients undergoing Cardio Pulmonary Bypass (CPB). Several measurements have been performed: before, during and after CPB.2.Development and optimization of a method allowing the detection of an uncoupling between central and peripheral arterial pressure thanks to AP signal analysis in real time and a potential complementary measurement performed with CATARSI.3.Several central to radial arterial modelling propositions in order to present a better evaluation of central arterial pressure estimated by radial arterial pressure
Nsiala-Nzéza, Crépin. "Récepteur adaptatif multi-standards pour les signaux à étalement de spectre en contexte non coopératif." Phd thesis, Université de Bretagne occidentale - Brest, 2006. http://tel.archives-ouvertes.fr/tel-00489462.
Повний текст джерелаSingh, Latchman. "Speech enhancement for forensic applications." Thesis, Queensland University of Technology, 1998. https://eprints.qut.edu.au/36080/1/36080_Singh_1998.pdf.
Повний текст джерелаKhan, Amir Ali. "Séparation de sources thermométriques." Phd thesis, Grenoble INPG, 2009. http://tel.archives-ouvertes.fr/tel-00477455.
Повний текст джерелаPoursoltan, Saman. "Bio-inspired vision model implementation in compressed surveillance videos." Thesis, 2015. http://hdl.handle.net/2440/95242.
Повний текст джерелаThesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 2015
(6634382), Deena Alabed. "Photoplythesmogram (PPG) Signal Reliability Analysis in a Wearable Sensor-Kit." Thesis, 2019.
Знайти повний текст джерелаIn recent years, there has been an increase in the popularity of wearable sensors such as electroencephalography (EEG) sensors, electromyography (EMG) sensors, gyroscopes, accelerometers, and photoplethysmography (PPG) sensors. This work is focused on PPG sensors, which are used to measure heart rate in real time. They are currently used in many commercial products such as Fitbit Watch and Muse Headband. Due to their low cost and relative implementation simplicity, they are easy to add to custom-built wearable devices.
We built an Arduino-based wearable wrist sensor-kit that consists of a PPG sensor in addition to other low cost commercial biosensors to measure biosignals such as pulse rate, skin temperature, skin conductivity, and hand motion. The purpose of the sensor-kit is to analyze the effects of stress on students in a classroom based on changes in their biometric signals. We noticed some failures in the measured PPG signal, which could negatively affect the accuracy of our analysis. We conjectured that one of the causes of failure is movement. Therefore, in this thesis, we build automatic failure detection methods and use these methods to study the effect of movement on the signal.
Using the sensor-kit, PPG signals were collected in two settings. In the first setting, the participants were in a still sitting position. These measured signals were manually labeled and used in signal analysis and method development. In the second setting, the signals were acquired in three different scenarios with increasing levels of activity. These measured signals were used to investigate the effect of movement on the reliability of the PPG sensor.
Four types of failure detection methods were developed: Support Vector Machines (SVM), Deep Neural Networks (DNN), K-Nearest Neighbor (K-NN), and Decision Trees. The classification accuracy is evaluated by comparing the resulting Receiver Operating Characteristic (ROC) curves, Area Above the Curve (AAC), as well as the duration of failure and non-failure sequences. The DNN and Decision Tree results are found to be the most promising and seem to have the highest error detection accuracy.
The proposed classifiers are also used to assess the reliability of the PPG sensor in the three activity scenarios. Our findings indicate that there is a significant presence of failures in the measured PPG signals at rest, which increases with movement. They also show that it is hard to obtain long sequences of pulses without failure. These findings should be taken into account when designing wearable systems that use heart rate values as input.