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Luo, Anqi, and Lei Ge. "Indoor Location Detection using WLAN." Thesis, KTH, Kommunikationssystem, CoS, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-91200.
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The thesis seeks to improve the accuracy of indoor wireless local area network (WLAN) location detection. The main task of the project is the design and analysis of a solution, which utilizes the packets which are already emitted by WLAN devices. The system consists of a signal receiver and signal processing. The positioning system does not transmit, thus the detection is completely passive. The result of measurements on received frames is used to calculate the WLAN transmitter's position. It does not require any transmissions, thus the detection is completely passive. The result of the measurements can be used to calculate the WLAN transmitter’s position. Location systems are more and more viewed as a necessary element of a WLAN system. Positioning accuracy is the most important issue in location system, especial in the indoor WLAN location detection. Indoor location systems are affected by indoor environment both due to multi-path and man-made effects. To resist these problems, we introduce a way to detect the arrival of the first instance of the signal by detecting the signal header. In our experiment, we timestamp the arrival of an IEEE 802.11b header. In our prototype the logic necessary to do this is implemented in an FPGA, specifically that of the Ettus Research USRP. The additional logic is quite small and might easily be added to the receiver in an access point, thus reducing the deployment cost of a location system in a real network. The proposed solution was experimentally verified. From our experiments, the detection works without requiring any changes to the hardware or software of the mobile device. By exploiting existing IEEE 802.11b transmissions the cost and difficulty of deployment is simplified due to the wide usage of IEEE 802.11b in mobile devices. Additionally, the preamble has good correlation properties making it is easy to detect the arrival of a IEEE 802.11frame. Our implementation is based upon open source hardware and software making it possible to implement this solution. A relatively low cost FPGA can be used as the correlation and timestamp circuit is rather simple (in terms of numbers of gates), making this solution feasible for commercial implementation. The method, implementation, testing, and analysis are presented in detail in the thesis.Avhandlingen syftar till att förbättra noggrannheten i inomhus trådlösa lokala nätverk (WLAN) placering upptäckt. Huvuduppgiften för projektet är design och analys av en lösning som utnyttjar paketen som redan avges av WLAN-enheter. Systemet består av en signal mottagare och signalbehandling. Det kräver inga transmissioner, alltså upptäckt är helt passiv. Resultatet av mätningarna kan användas för att beräkna WLAN-sändarens läge. Målet är att förbättra noggrannheten i inomhus plats uppskattning. Läge system alltmer ses som en nödvändig del av WLAN system. Positioneringsnoggrannheten ses som den viktigaste frågan i läge system, speciellt för inomhusbruk WLAN baserade location. Läge system påverkas mer av inomhusmiljöer än utemiljön, eftersom det finns mer multi-path fading och konstgjorda effekter. Att minska dessa problem, vi införa ett sätt att känna av signalen ankomst genom att förbättra upptäckten av ankomsten av IEEE 802.11-huvudet. Detta kan bidra till att besegra multipath effekt och enkla metoden skulle kunna minska kostnaderna för placering i framtiden kopplingspunkter. Den föreslagna lösningen har verifierats experimentellt. Från vårt experiment fungerar upptäckt utan att kräva några ändringar i hårdvara eller mjukvara för den mobila enheten. Genom att utnyttja befintliga IEEE 802.11b sändningar kostnaden och svårigheten att utbyggnaden är förenklad på grund av den breda användningen av IEEE 802.11b i mobila enheter. Dessutom "preamble" har god korrelation egenskaper som gör det lätt att upptäcka ankomsten av en IEEE 802.11-ramen. Vår genomfört bygger på öppen källkod maskin-och programvara som gör det möjligt att genomföra denna lösning. En relativt låg kostnad FPGA kan användas som korrelation och tidstämpel kretsen är ganska enkel (i termer av antalet logikelement), vilket gör denna lösning vara möjlig för kommersiell tillämpning. Metoden, implementation, testning och analys presenteras i detalj i avhandlingen.
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Pal, Maninder. "Leak detection and location in polyethylene pipes." Thesis, Loughborough University, 2008. https://dspace.lboro.ac.uk/2134/15181.
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This thesis is focused on the application of cross-correlation technique for leak detection and location in medium density polyethylene (MDPE) pipes. A leaking water pipe generates noise that depends primarily on water pressure, pipe characteristics and the leak size and shape. This noise, commonly called leak signals, can be used for the purpose of leak detection and leak location in MDPE pipes. A correlation technique is typically employed to detect, position and characterise these water leaks and is proved to be very efficient for metallic pipes. However, the same is not true for MDPE pipes where the attenuation rate with distance of the leak/source signal is very high, and the generated leak signals are of low frequency and narrow bandwidth. In order to locate leak with good accuracy in MDPE pipes, the correlation process relies on the estimation of speed of leak signals in water/pipe and the time delay between leak signals measured at two locations. For time delay estimation, a correlation function is used. Its accuracy depends upon the sharpness of the correlation peak, type and positioning of sensor, and the processing of signals obtained, which in turn further depends upon the characteristics of leak signals. In MDPE pipes, leak signals are of low frequency and narrow bandwidth; however, their frequency response is not well characterised. Therefore, this thesis presents an analytical model to explain the acoustic characteristics of leak signals in MDPE pipes. The model is used to study the effects of the cut-off frequencies of low, high and band pass digital filters and the selection of acoustic/vibration sensors for the correlation technique. It detailed the importance of the cut-off frequency of the high pass filter and the insensitivity of the correlation function to the cut off frequency of the low pass filter.
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Lee, Jeong Heon. "Physical Layer Security for Wireless Position Location in the Presence of Location Spoofing." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/26417.
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While significant research effort has been dedicated to wireless position location over the past decades, most location security aspects have been overlooked. Recently, with the proliferation of diverse wireless devices and the desire to determine their position, there is an increasing concern about the security of location information which can be spoofed or disrupted by adversaries or unreliable signal sources. This dissertation addresses the problem of securing a radio location system against location spoofing, specifically the characterization, analysis, detection, and localization of location spoofing attacks by focusing on fundamental location estimation issues.
The objective of this dissertation is four-fold. First, it provides an overview of fundamental security issues for position location, particularly associated with range-based localization. Of particular interest are security risks and vulnerabilities in location estimation, types of localization attacks, and their impact. The second objective is to characterize the effects of signal strength and beamforming attacks on range estimates and the resulting position estimate. The characterization can be generalized to a variety of location spoofing attacks and provides insight into the anomalous behavior of range and location estimators when under attack. Through this effort we can also identify effective attacks that are of particular interest to attack detection and localization. The third objective is to develop an effective technique for attack detection which requires neither prior environmental nor statistical knowledge. This is accomplished by exploiting the bilateral behavior of a hybrid framework using two received signal strength (RSS) based location estimators. We show that the resulting approach is effective at detecting attacks with the detection rate increasing with the severity of the induced location error. The last objective of this dissertation is to develop a localization method resilient to attacks and other adverse effects.
Since the detection and localization approach relies solely on RSS measurements in order to be applicable to a wide range of wireless systems and scenarios, this dissertation focuses on RSS-based position location. Nevertheless, many of the basic concepts and results can be applied to any range-based positioning system.Ph. D.
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Groh, Brittany Nicole. "Impact of Expressive Intensity and Stimulus Location on Emotion Detection." TopSCHOLAR®, 2017. https://digitalcommons.wku.edu/theses/2020.
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Previous research demonstrates that the age of an observer, the peripheral location of a face stimulus on a display, and the intensity of the emotion expressed by the face all play a role in emotion perception. Older individuals have more difficulty identifying emotion in faces, especially at lower expressive intensities. The purpose of the current study was to understand how younger and older adults’ abilities to detect emotion in facial stimuli presented in the periphery would be affected by the intensity of the emotional expressions and the distance that the expressions are presented away from the center of the display. The current study presented facial stimuli for a short duration to bypass reactionary attentional influences. More intense fearful and angry expressions were expected to be easier to classify for both younger and older adults than lower intensity expressions, but all expressions were expected to become more difficult to classify when presented further in the periphery. Older adults and younger adults displayed similar emotion detection for typical and extreme intensity angry expressions and for high intensity fearful expressions. However, older adults struggled to detect typical intensity fear, and this deficit grew with the angle of eccentricity from which the stimuli were presented from the center of the display. Possible explanations for these age differences are discussed.
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Haider, Raja Umair. "Fault Detection in WLAN Location Fingerprinting Systems Using Smartphone Inertial Sensors." Thesis, Linköpings universitet, Kommunikationssystem, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-81940.
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Indoor positioning is a rapidly growing research area, enabling new innovative location-aware applications and user-oriented services. Location Fingerprinting (LF) is the positioning technique of coupling a physical location with observed radio signal measurements. In the terms of indoor LF using Wireless Local Area Network (WLAN) it refers to the use of network measurements from the WLAN Access Points (APs) to tag known locations. A data set is created containing reference fingerprints for the area of interest and is known as a radio map. A radio map can later be used to find a user's location in the area of interest. WLAN infrastructures are vulnerable to many kinds of faults and malicious attacks, including, an attacker jamming the signal from an AP, or an AP becoming unavailable during positioning due to power outage. These faults can be collectively characterized as an AP-failure. In LF positioning systems, AP-failure faults can significantly degrade the performance of a LF system due to the difference between the current fingerprints and radio map created with all APs being available. It is desirable to detect such faulty APs, in order to take actions towards fault-mitigation and restoration, in case of a malicious attack. In this work, we have developed a fault detection algorithm that uses inertial sensors (i.e., accelerometer, magnetometer) available in smartphones to detect AP-failure faults in LF systems. Inertial Measurement Unit (IMU) has become an integral part of all high-end smartphones. IMU can be used to infer location information on the smartphone. The main idea is to have two parallel position streams, the LF positioning and the IMU positioning, and to compare the mean positioning error between the two. Since IMU positioning is fairly accurate once provided with starting coordinates, we use it to detect abnormal behaviour in LF positioning system, such as highly erroneous estimates signifying an AP-failure fault present in the system. The performance of the proposed detection algorithm is evaluated with several real-life AP-related faults. The proposed algorithm exhibits low probability of false alarms in the detection of faulty APs. The conclusion is that using IMU based positioning is an effective and robust solution in terms of fault detection in LF systems.
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Frimpong, George Kwabena. "Acoustic detection and location of partial discharges in power transformer tanks." Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/15708.
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Gené, Mola Jordi. "Fruit detection and 3D location using optical sensors and computer vision." Doctoral thesis, Universitat de Lleida, 2020. http://hdl.handle.net/10803/669110.
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Per tal de satisfer les necessitats alimentàries d’una població mundial creixent, és necessari optimitzar la producció agrícola, incrementant la productivitat i la sostenibilitat de les explotacions. Per aconseguir-ho, es preveu que els sistemes automàtics de detecció i localització de fruits seran una eina essencial en la gestió de les plantacions fructícoles, amb aplicacions directes a la predicció de la collita, el mapat de la producció i la recol·lecció automatitzada. Malgrat els avenços aconseguits en àmbits com la robòtica o la visió per computador, la localització 3D de fruits continua essent un repte que ha de fer front a problemes com la identificació de fruits oclosos per altres òrgans vegetatius, o la possibilitat de treballar en diferents condicions d’il·luminació. La present tesi pretén contribuir en el desenvolupament de noves metodologies de detecció i localització de fruits mitjançant la combinació de sensors de base fotònica i d’algoritmes de visió artificial. Per tal de minimitzar els efectes produïts per unes condicions d’il·luminació variable, es proposa l’ús de sensors actius que treballen en l’espectre de llum infraroja. En concret, s’han testejat sensors LiDAR (light detection and ranging) i càmeres de profunditat (RGB-D) basades en el principi de temps de vol (time-of-flight), els quals proporcionen els valors d’intensitat de llum reflectida pels diferents elements mesurats. D’altra banda, per minimitzar el número d’oclusions s’han estudiat dues estratègies: (1) l’aplicació forçada d’aire; (2) la utilització de tècniques d’escaneig des de diferents punts de vista, com ara Structure-from-Motion (SfM). Els resultats obtinguts demostren que les dades d’intensitat proporcionades pels sensors actius LiDAR i RGB-D són de gran utilitat per la detecció de fruits, el que suposa un avanç en l’estat de l’art, ja que aquesta capacitat radiomètrica no havia estat estudiada anteriorment. D’altra banda, les dues estratègies testejades per minimitzar el número de fruits oclosos han demostrat incrementar el percentatge de fruits detectats. De totes les metodologies estudiades, la combinació de xarxes neuronals profundes amb tècniques de SfM és la que presenta més bons resultats, amb percentatges de detecció superiors al 90% i menys d’un 4% de falsos positius.Para satisfacer las necesidades alimentarias de una población mundial creciente, es necesario optimizar la producción agrícola, incrementando la productividad y la sostenibilidad de las explotaciones. Para conseguirlo, se prevé que los sistemas automáticos de detección y localización de frutos serán una herramienta esencial en la gestión de las plantaciones frutícolas, con aplicaciones directas a la predicción de cosecha, al mapeado de la producción y a la recolección automatizada. A pesar de los avances conseguidos en ámbitos como la robótica o la visión artificial, la localización 3D de frutos continua siendo un reto que debe de hacer frente a problemas como la identificación de frutos ocluidos por otros órganos vegetativos, o la posibilidad de trabajar en distintas condiciones de iluminación. La presente tesis pretende contribuir en el desarrollo de nuevas metodologías de detección y localizacion de frutos mediante la combinación de sensores de base fotónica y de algoritmos de visión artificial. A fin de minimizar los efectos producidos por unas condiciones de iluminación variable, se propone el uso de sensores activos que trabajan en espectros de luz infrarroja. En concreto, se han testeado sensores LiDAR (light detection and ranging) y cámaras de profundidad (RGB-D) basadas en el principio de tiempo de vuelo (time-of-flight), los cuales proporcionan valores de intensidad de la luz reflejada por los objetos escaneados. Por otra parte, para minimizar el número de oclusiones se han estudiado dos estrategias: (1) la aplicación forzada de aire; (2) la utilización de técnicas de escaneo desde distintas perspectivas, tales como Structure-from-Motion (SfM). Los resultados obtenidos demuestran que los datos de intensidad proporcionados por los sensores LiDAR y RGB-D son de gran utilidad para la detección de frutos, lo que supone un avance en el estado del arte, ya que esta capacidad radiométrica no había estado estudiada anteriormente. Por otra parte, las dos estrategias testeadas para minimizar el número de oclusiones han demostrado incrementar el porcentaje de detección. De todas las metodologías estudiadas, la combinación de redes neuronales profundas con técnicas de SfM es la que presenta mejores resultados, con porcentajes de detección superiores al 90% y con menos de un 4% de falsos positivos.
To meet the food demands of an increasing world population, farmers are required to optimize agriculture production by increasing crop productivity and sustainability. To do so, fruit detection and 3D location systems are expected to be an essential tool in the agricultural management of fruit orchards, with applications in fruit prediction, yield mapping, and automated harvesting. Despite the latest advances in robotics and computer vision, the development of a reliable system for 3D fruit location remains a pending issue to deal with problems such as the identification of occluded fruits and the variable lighting conditions of agricultural environments. The present thesis aims to contribute to the development of new methodologies for fruit detection and location by combining optical sensors and artificial intelligence algorithms. In order to minimize variable lighting effects, it is proposed the use of active sensors that work in the infrared light spectrum. In particular, light detection and ranging sensors (LiDAR) and depth cameras (RGB-D) based on the time-of-flight principle were evaluated. These sensors provide the amount of backscattered infrared light reflected by the measured objects. With respect to minimizing the number of fruit occlusions, two different approaches were tested: (1) the application of forced air flow; and (2) the use of multi-view scanning techniques, such as structure-from-motion (SfM) photogrammetry. The results have demonstrated the usefulness of the backscattered intensity provided by LiDAR and RGB-D sensors for fruit detection. This supposes an advance in the state-of-the-art, since this feature has not previously been exploited. Both of the strategies tested to minimize fruit occlusions showed an increase in the fruit detection rate. Of all the tested methodologies, the combination of instance segmentation neural networks and SfM photogrammetry gave the best results, reporting detection rates higher than 90% and false positive rates under 4%.
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Farley, Ben. "Optimal sensor placement for detection and location of leak/burst events." Thesis, University of Sheffield, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.541990.
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Tan, Qinling Jeanette Olivia. "Passive coherent detection and target location with multiple non-cooperative transmitters." Thesis, Monterey, California: Naval Postgraduate School, 2015. http://hdl.handle.net/10945/45951.
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Approved for public release; distribution is unlimitedPassive bistatic radars (PBR) and passive multistatic radars (PMR) use opportunistic transmitters to detect and locate targets. In this thesis, a maritime scenario was modeled with merchant vessels serving as multiple non-cooperative opportunistic transmitters while a frigate warship equipped with Electronic Warfare (EW) and Direction Finding (DF) receivers takes on the role of the receiver in a PBR/PMR configuration. The targets are assumed to be the generic Formidable-class frigate. A MATLAB model is developed to simulate the operating environment and passive detection and location process. Detection coverage is investigated to propose optimal PBR/PMR configurations and geometry, while elliptical and hyperbolic target location methods are explored to quantify the effects of PBR/PMR parameters and geometry on target estimated location uncertainty.
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Loos, Matthieu. "Single phase to ground fault detection and location in compensated network." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209544.
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This work takes place in the context of distribution power system protection and tries to improve the detection and location of earth faults. The protection problem is vast and many ideas emerge every year to enhance the reliability of the grid. The author has focused his energy into the compensated and isolated network protection in the specific case of single phase earth fault. This PhD thesis is divided in two main parts that might be considered as independent. The first part studies the detection of single phase earth fault and the second analyzes the fault location of such fault.Pragmatism was asked during these three years because a product development was necessary especially regarding the fault detection problem. The first part of the thesis took 18 months of research and development to obtain a prototype of transient protection able to detect single phase earth fault in compensated and isolated network. The sensitivity of the algorithm has been emphasized regarding the fault impedance and to detect earth fault up to 5 kOhm depending on the network characteristic. The fault location problem has been much more theoretical although the problem links to the accuracy of the algorithm and its robustness regarding wrong fault location indication has been strongly considered.
Compensated networks and in some conditions isolated networks are distribution from 12 kV up to 110 kV mostly used in East and North Europe but also in China. Others areas also work with such networks but they also have others systems and they do not use them on all the territory. These networks have the particularity to obtain very small fault current in case of single phase earth fault. Low current means the difference between a faulty and a sound feeder is not significant. Therefore classic overcurrent protection is completely useless to protect the network, forcing the development of more complex algorithm. A possibility to overcome the problem of the small fault current is to develop a transient protection. The transient occurring at the beginning of the fault has strong information to distinguish a faulty from a sound feeder. In this work I have chosen to use not only the transient but also the steady state to get the best sensitivity.
Then the fault location has been investigated but the small information coming from the faulty feeder is not sufficient to have a precise enough position of the fault. Therefore, active system has been suggested to be implemented in the grid to increase the faulty current and have enough power for a precise location. Different existing algorithms based on the steady state at the nominal frequency are compared using a tool developed during this work. Recommendations are then made depending on the topology, the network parameters, the measurements precision, etc. Due to the complexities of the problem, a simulator has been coded in Matlab .The user of a possible fault location must then use this tool to understand and see the future fault location precision that he could obtain from different algorithm on his network.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished
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Wang, Xinheng. "Characterization, detection and location of sheath fault on underground power transmission cables." Thesis, Brunel University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367857.
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RezaeiDivkolaei, Pouya. "DETECTION, CLASSIFICATION, AND LOCATION IDENTIFICATION OF TRAFFIC CONGESTION FROM TWITTER STREAM ANALYSIS." OpenSIUC, 2017. https://opensiuc.lib.siu.edu/theses/2257.
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Social media today is an important source of information about various events happening around the world. Among various social networking platforms, microtext based ones such as Twitter are of special interest as they are also a rich source of real-time events. In this thesis, our goal is to study the effectiveness of using Twitter as a social sensor for obtaining real-time information on road traffic conditions. Specifically, we focus on: i) identifying tweets that contain traffic event related information, ii) classify such tweets into six main groups of accident, fire, road construction, police activities, weather and others, iii) extract fine-grained location information about the traffic incident by analyzing tweet text. Our experimental results show that using Twitter as a social sensor for obtaining rich information about traffic events is indeed a promising approach. We show that we can correctly detect traffic related tweets with an accuracy of 81%. Moreover, the accuracy of correctly classifying traffic related tweets into one of the six categories is 97%. Lastly, our experimental results show that using only geo-tags of tweets is not sufficient for fine-grained localization of traffic incidents due to two reasons: i) a vast majority of traffic related tweets do not contain geo-tags, and ii) the location mentioned in the tweet text and the geo-tag of a tweet do not always agree. Such observations prove that fine-grained localization of traffic incidents from tweet must also include analysis of the tweet text using Natural Language Processing techniques.
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Wang, Hao. "Two-Stage Fault Location Detection Using PMU Voltage Measurements in Transmission Networks." Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/54565.
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Fault location detection plays a crucial role in power transmission network, especially on security, stabilization and economic aspects. Accurate fault location detection in transmission network helps to speed up the restoration time, therefore, reduce the outage time and improve the system reliability [1]. With the development of Wide Area Measurement System (WAMS) and Phasor Measurement Unit (PMU), various fault location algorithms have been proposed.
The purpose of this work is to determine, modify and test the most appropriate fault location method which can be implemented with a PMU only linear state estimator. The thesis reviews several proposed fault location methods, such as, one-terminal [2], multi-terminal [3]-[11] and travelling wavelets methods [12]-[13]. A Two-stage fault location algorithm using PMU voltage measurements proposed by Q. Jiang [14] is identified as the best option for adaption to operate with a linear state estimator. The algorithm is discussed in details and several case studies are made to evaluate its effectiveness. The algorithm is shown to be easy to implement and adapt for operation with a linear state estimator. It only requires a limited number of PMU measurements, which makes it more practical than other existing methods. The algorithm is adapted and successfully tested on a real linear state estimator monitored high voltage transmission network.Master of Science
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Abboud, Layane. "Time Reversal techniques applied to wire fault detection and location in wire networks." Phd thesis, Supélec, 2012. http://tel.archives-ouvertes.fr/tel-00771964.
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In this thesis we present new approaches in the domains of soft fault detection and location in complex wire networks, based on the properties of time reversal. When addressing the detection of soft faults, the idea is to adapt the testing signal to the network under test, instead of being predefined for all the tested networks, as opposed to standard reflectometry techniques. We prove that this approach, which we name the Matched Pulse approach (MP), is beneficial whenever the system is more complex, i.e., its response is richer in echoes, which is opposed to common understanding. The MP analysis is conducted via a formal mathematical analysis, followed by simulation and experimental results validating the proposed approach. In the domain of soft fault location, and based on the DORT (Décomposition de l'Opérateur de Retournement Temporel) properties, we derive a distributive non-iterative method able to synthesize signals that focus on the fault position. Through a statistical study we analyze some of the influencing parameters on the performance of the method, and then simulation and experimental results show that the method is able to synthesize signals directly focalizing on the soft fault position, without the need for iterations.
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Du, Pisani Renaldo Murray. "Design of an Underwater Object Detection and Location System using Wide-Beam SONAR." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/86236.
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Thesis (MScEng)--Stellenbosch University, 2014.ENGLISH ABSTRACT: This thesis describes the second project relating to the development of a SONAR (SOund Navigation And Ranging) object detection and collision avoidance system for use on an AUV (Autonomous Underwater Vehicle) at Stellenbosch University. The main goal is to develop and test techniques that make use of the existing SONAR laboratory platform and wide-beam SONAR transducers to detect and locate objects and their limits/bounds under water in the horizontal plane. The results of the work done show that it is possible to use wide-beam transducers to locate the centroid and edges of a flat target with an error that is significantly smaller than the beam-width. The techniques developed will enable the development of a cost-effective SONAR system that can be implemented on an AUV.
AFRIKAANSE OPSOMMING: Hierdie tesis beskryf the tweede projek rakende die ontwikkeling van ’n SONAR voorwerp opsporings en botsingvermydingstelsel vir gebruik op ’n OOV (Outonome Onderwater Voertuig) aan die Universiteit van Stellenbosch. Die hoofdoel is om tegnieke te ontwikkel en te toets wat gebruik maak van die bestaande SONAR laboratorium opstelling en wye-straal SONAR opnemers om die posisie van voorwerpe onder water te bepaal, sowel as die posisie van die voorwerp se rande in die horisontale vlak. Die resultate van die werk wat gedoen is wys dat dit moontlik is om wye-straal opnemers te gebruik om die posisie van die sentroïde en rande van ’n plat voorwerp te vind met ’n fout wat aansienlik kleiner is as die straal-wydte. Die tegnieke wat ontwikkel is sal ons in staat stel om ’n koste-effektiewe SONAR stelsel te ontwikkel wat op ’n OOV geïmplenteer kan word.
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Song, Lijun. "Detection and Position Location of Partial Discharges in Transformers Using Fiber Optic Sensors." Thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/35928.
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Power transformers are one of the most important components in the electrical energy network. Extending transformer life is very economically valuable due to power outage. Therefore the development of instruments to monitor the transformer condition is of great interest. Detection of partial discharges (PDs) in power transformers is an effective diagnostic because it may reveal and quantify an important aging factor and provide information on the condition of the transformer. However, partial discharge diagnostics are still not effectively used for online monitoring of transformers because of the complexity of PD measurements and difficulties of discriminating of PDs and other noise sources.
This thesis presents a further study of detection and location of partial discharges in power transformers based on previous work conducted at the Center for Photonics Technology (CPT) at Virginia Tech. The detection and positioning system consists of multiple extrinsic Fabry-Parot interferometric (EFPI) fiber acoustic sensors which can survive the harsh environment of oil-filled transformers.
This thesis work is focused on optimal arrangement of multiple sensors to monitor and locate PD activities in a power transformer. This includes the following aspects. First, the sensor design requirements are discussed in order to successfully detect and accurately position the PD sources. In the following sections, Finite Element Method (FEM) is used to model the EFPI sensor fabricated at CPT. Experiments were conducted to measure the angular dependence of the frequency response of the sensor. It is shown that within the range of ±45º incident angles, the sensitivity varies by 3-5dB. Finally, the thesis demonstrates a PD positioning experiment in a 500 gallon water tank (R à H = 74" à 30" cylinder) using a hyperbolic positioning algorithm and time difference of arrival (TDOA). Finally we demonstrated that 100% of the positioning data is bounded by a 22.7à 4.1à 5.3 mm3 cube, with a sensing range of 810 mm using the leading edge method with FIR filtering.Master of Science
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Verdon-Roe, Gay Mary. "Development of a multi-location motion displacement test for detection of early glaucoma." Thesis, University College London (University of London), 2006. http://discovery.ucl.ac.uk/1445896/.
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This thesis describes the development of a multi-location motion displacement test (MDT) for the early detection of glaucoma. The test uses line displacement stimuli, which are orientated with the retinal nerve fibre layer (RNFL) and scaled with ganglion cell density. Psychophysical properties of hyperacuity motion displacement were explored and results applied to optimize the stimulus presentation and test format. Investigations included the following: (i) Optical blur: MDT was found to be robust to peripheral astigmatism. The effect of spherical blur was quantified and the implication for discrimination between glaucoma and normal discussed. (ii) Spatial summation properties: equivalent MDT thresholds were demonstrated for equivalent length of single and multi-line stimuli. Equivalent MDT thresholds were also found for stimuli of equivalent energy ( stimulus area * stimulus luminance - background luminance ), in accordance with Ricco's Law. A linear relationship (slope 0.5) was found between log MDT threshold and log relative stimulus energy. A new law is proposed to apply to MDT summation properties, giving the relationship T = KVE T = MDT threshold K = constant E = stimulus energy . This may be used to predict MDT threshold for different configurations of stimuli. (iii) Shortening of response time was observed as stimulus duration is reduced and explained by altered temporal summation properties. The results were applied to modify the subject response window, with benefit of reduced test duration. (iv) Selection of stimulus number and position was made by study of attention, together with application of the anatomical relationship of the RNFL with the optic nerve head. (v) A staircase strategy was developed. Parameters were selected by analysis of results gained within the PhD and earlier studies. Results were pooled to accomplish an operational test. Preliminary assessment indicates that focal glaucomatous defects detected by standard automated perimetry are replicated by the new MDT.
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Drew, J. "Coalescence microseismic mapping : an imaging method for the detection and location of seismic events." Thesis, University of Cambridge, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.598649.
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The Coalescence Microseismic Mapping method I have developed is applicable to event detection and location for a sparse array, while still benefiting from rigorous statistical analysis by averaging data over the array. Formulated within a Bayesian framework with respect to traveltime, the automated method simultaneously identifies and quantitatively images source location, by mapping a scalar signal that characterizes both the presence and timing of a seismic arrival. Unlike traveltime inversion, the numerical approach is not restrictive in regards to the type and distribution of errors. Effectively providing the probability density functions, the approach also allows for new ways to aggregate, visualize and interpret the results. Signal phase information can be assimilated in the solution when this can be recovered from the data, with the potential for improving location resolution. The method can be incorporated within a general integrated workflow, including an iterative or global inversion for multiple parameters. The theory is discussed in detail then applied to two datasets. The first is the integrated analysis of data acquired by a surface array deployed in the vicinity of Askja Volcano, Iceland. Here the signal phase information is recovered after correction for shear wave splitting and compensation for attenuation and station response. The second is for data acquired by a sub-surface array, monitoring seismic activity associated with hydraulic fracturing of a hydrocarbon reservoir. In this example the location is further constrained by including weighted signal polarization information in the search.
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Linford, Paul William. "The application of signal processing techniques to leak detection and location in water pipes." Thesis, University of East Anglia, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.250640.
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Markalous, Sacha M. "Detection and location of partial discharges in power transformers using acoustic and electromagnetic signals /." Göttingen : Sierke, 2007. http://deposit.d-nb.de/cgi-bin/dokserv?id=2958679&prov=M&dok_var=1&dok_ext=htm.
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Souto, Laiz. "Data-driven approaches for event detection, fault location, resilience assessment, and enhancements in power systems." Doctoral thesis, Universitat de Girona, 2021. http://hdl.handle.net/10803/671402.
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This thesis presents the study and development of distinct data-driven techniques to support event detection, fault location, and resilience assessment towards enhancements in power systems. It is divided in three main parts as follows. The first part investigates improvements in power system monitoring and event detection methods with focus on dimensionality reduction techniques in wide-area monitoring systems. The second part focuses on contributions to fault location tasks in power distribution networks, relying on information about the network topology and its electrical parameters for short-circuit simulations over a range of scenarios. The third part assesses enhancements in power system resilience to high-impact, lowprobability events associated with extreme weather conditions and human-made attacks, relying on information about the system topology combined with simulations of representative scenarios for impact assessment and mitigation. Overall, the proposed data-driven algorithms contribute to event detection, fault location, and resilience assessment, relying on electrical measurements recorded by intelligent electronic devices, historical data of past events, and representative scenarios, together with information about the network topology, electrical parameters, and operating status. The validation of the algorithms, implemented in MATLAB, is based on computer simulations using network models implemented in OpenDSS and SimulinkEsta tesis presenta el estudio y el desarrollo de distintas técnicas basadas en datos para respaldar las tareas de detección de eventos, localización de fallos y resiliencia hacia mejoras en sistemas de energía eléctrica. Los contenidos se dividen en tres partes principales descritas a continuación. La primera parte investiga mejoras en el monitoreo de sistemas de energía eléctrica y métodos de detección de eventos con enfoque en técnicas de reducción de dimensionalidad en wide-area monitoring systems. La segunda parte se centra en contribuciones a tareas de localización de fallos en redes eléctricas de distribución, basándose en información acerca de la topología de la red y sus parámetros eléctricos para simulaciones de cortocircuito en una variedad de escenarios. La tercera parte evalúa mejoras en la resiliencia de sistemas de energía eléctrica ante eventos de alto impacto y baja probabilidad asociados con condiciones climáticas extremas y ataques provocados por humanos, basándose en información sobre la topología del sistema combinada con simulaciones de escenarios representativos para la evaluación y mitigación del impacto. En general, los algoritmos propuestos basados en datos contribuyen a la detección de eventos, la localización de fallos, y el aumento de la resiliencia de sistemas de energía eléctrica, basándose en mediciones eléctricas registradas por dispositivos electrónicos inteligentes, datos históricos de eventos pasados y escenarios representativos, en conjunto con información acerca de la topología de la red, parámetros eléctricos y estado operativo. La validación de los algoritmos, implementados en MATLAB, se basa en simulaciones computacionales utilizando modelos de red implementados en OpenDSS y Simulink
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Reza, Hasnain. "Detection, location, and trajectory tracing of moving objects in the real world two-dimensional images." Ohio : Ohio University, 1988. http://www.ohiolink.edu/etd/view.cgi?ohiou1182869492.
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Ghaderi, Abbas. "Self-powered system for the detection and location of faulted insulators in overhead distribution power lines." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017.
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Post insulators as the weakest component of transmission lines, are highly exposed to breakdown. Insulators breakdown leads to outage and economic loss for transmission companies. Faulted post insulator detection and location is very important to minimum duration of outage. Depending on type of post insulators types, they can be detected in case of breakdown. Silicon rubber post insulators as new generation of insulators, have better insulation characteristics compare to others. Away from all of its advantages, detection and location of broken ones are difficult for system operator due to no external damage. In this thesis design of a self-powered system to detect the broken silicon rubber post insulator has been pursued. An innovative optical effect triggered by self-powered system has been deployed to detect faulted post insulator.
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Olugboji, Oluwafemi A. "Development of a monitoring system for detection, location and assessment of impact events in petroleum pipelines." Thesis, University of Newcastle Upon Tyne, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.555980.
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Third party damage to petroleum pipelines can be catastrophic if undetected. This damage results in financial losses, environmental pollution and frequent loss of life as a result of explosion. Therefore damage detection and location methods will play a key role in the overall integrity management of a pipeline system. This thesis presents the development and testing of mathematical techniques for locating an impulsive event on a pipeline and reconstructing the pressure pulse caused by it from measurements made remotely. When an impulsive event occurs along a pipeline, the pressure pulse propagates in both directions and can be detected and measured by sensors located at different positions along the pipeline. From these measurements the location of the event can be determined and its form reconstructed. Techniques for reconstructing the pulse at it source from the distorted pulses measured were developed using deconvolution theory and inverse methods. This theoretical work was validated by experiments using a simulated pipeline. The experimental work was carried out using an experimental test rig comprising a flexible hose pipe 23 m long and 19 mm diameter with four pressure sensors distributed along the pipe and connected to a data acquisition system. The techniques were tested for both static and flowing air in the pipe, and were found to give good results. Finally, an outline design was produced for a monitoring system suitable for use in the field. The principal components were identified and costed and the power requirement determined. From this it was shown that a system of that type could be constructed at a realistic price.
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Schaeffer, Paul J. "AUTOMATED ACOUSTIC DETECTION AND PROCESSING FOR THE ADVANCED RANGE INSTRUMENTATION AIRCRAFT SONOBUOY MISSILE IMPACT LOCATION SYSTEM." International Foundation for Telemetering, 1991. http://hdl.handle.net/10150/612914.
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International Telemetering Conference Proceedings / November 04-07, 1991 / Riviera Hotel and Convention Center, Las Vegas, NevadaRecent advances in acoustic detection and array processing have led to a new, state of the art, Sonobuoy Missile Impact Location System (SMILS). This system was developed for the 4950th Test Wing by E-Systems and the Johns Hopkins University Applied Physics Laboratory to support ballistic missile testing in broad ocean areas. The hardware and software required to perform the SMILS mission were developed in two different areas: 1) The flight system, installed aboard the Advanced Range Instrumentation Aircraft (ARIA), which provides everything necessary to guide the aircraft to the target area of Deep Ocean Transponders (DOTs), deploy sonobuoys, recover signals from the sonobuoys, and to process the recovered signals. The sonobuoy positions and impact locations of reentry vehicles are determined aboard the aircraft in real-time by telemetering the acoustic signals sent from the sonobuoys via Radio Frequency (RF) link to the aircraft. These acoustic signals are also recorded on analog tape in the aircraft. 2) The Post Mission Analysis System (PMAS), located at the 4950th Test Wing, processes the analog tapes recorded by the aircraft to do more sophisticated Processing than that performed on the aircraft, providing higher resolution of impact times and positions. This paper addressees the theory of PMAS operation and the specific approach used to perform automated acoustic detection of both narrow and wide band acoustic signals. It also addressees the processing technique employed to determine sonobuoy navigation and impact scoring.
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Liu, Zhi. "Location Estimation and Geo-Correlated Information Trends." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc1062799/.
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A tremendous amount of information is being shared every day on social media sites such as Facebook, Twitter or Google+. However, only a small portion of users provide their location information, which can be helpful in targeted advertising and many other services. Current methods in location estimation using social relationships consider social friendship as a simple binary relationship. However, social closeness between users and structure of friends have strong implications on geographic distances. In the first task, we introduce new measures to evaluate the social closeness between users and structure of friends. Then we propose models that use them for location estimation. Compared with the models which take the friend relation as a binary feature, social closeness can help identify which friend of a user is more important and friend structure can help to determine significance level of locations, thus improving the accuracy of the location estimation models. A confidence iteration method is further introduced to improve estimation accuracy and overcome the problem of scarce location information. We evaluate our methods on two different datasets, Twitter and Gowalla. The results show that our model can improve the estimation accuracy by 5% - 20% compared with state-of-the-art friend-based models.
In the second task, we also propose a Local Event Discovery and Summarization (LEDS) framework to detect local events from Twitter. Many existing algorithms for event detection focus on larger-scale events and are not sensitive to smaller-scale local events. Most of the local events detected by these methods are major events like important sports, shows, or big natural disasters. In this work, we propose the LEDS framework to detect both bigger and smaller events. LEDS contains three key steps: 1) Detecting possible event related terms by monitoring abnormal distribution in different locations and times; 2) Clustering tweets based on their key terms, time, and location distribution; and 3) Extracting descriptions include time, location, and key sentences of local events from clusters. The model is evaluated on a real-world Twitter dataset with more than 60 million tweets. The analysis of Twitter data can help to predict or explain many real-world phenomena. The relationships among events in the real world can be reflected among the topics on social media. In the third task, we propose the concept of topic association and the associated mining algorithms. Topics with close temporal and spatial relationship may have direct or potential association in the real world. Our goal is to mine such topic associations and show their relationships in different time-region frames. We propose to use the concepts of participation ratio and participation index to measure the closeness among topics and propose a spatiotemporal index to calculate them efficiently. With the topic filtering and the topic combination, we further optimize the mining process and the mining results.
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Gu, Xiaohan, and Ling Yang. "Face detection based on skin color." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-13767.
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This work is on a method for face detection through analysis of photos. Accurate location of faces and point out the faces are implemented. In the first step, we use Cb and Cr channel to find where the skin color parts are on the photo, then remove noise which around the skin parts, finally, use morphology technique to detect face part exactly. Our result shows this approach can detect faces and establish a good technical based for future face recognition.
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Jalali, Jalal. "Artificial neural networks for reservoir level detection of CO₂ seepage location using permanent down-hole pressure data." Morgantown, W. Va. : [West Virginia University Libraries], 2010. http://hdl.handle.net/10450/11137.
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Thesis (Ph. D.)--West Virginia University, 2010.Title from document title page. Document formatted into pages; contains xii, 140 p. : ill. (some col.), col. maps. Includes abstract. Includes bibliographical references (p. 99-104).
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Talukder, Md Shapon Shapon. "CONTINUOUS LOCATION FINDING AND COLLISION AVOIDANCE WITH OBJECT DETECTION USING IMAGE PROCESSING AN ASPECT OF ROBOTIC VISION." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/theses/1464.
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In this thesis, I propose a method for finding the location of a moving robot in an arena. In scenarios where a robot need to reach a goal by evading obstacles or collision avoidance and perpetually calculating distance from the object, it is indispensable for the robot token precisely where it is. I propose an image processing with a color base approach to find the solution to this quandary. The main conception is to find some reference objects from the images captured by a camera and find a mapping between the size of the object in the image and the physical distance of the object. Amalgamating the distance information from multiple reference points I can facilely find the position of the robot in the arena. Experimental results reveal the prosperity of the proposed technique by engendering highly precise results.
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Kelly, Brendan T. "A Newly Proposed Method for Detection, Location, and Identification of Damage in Prestressed Adjacent Box Beam Bridges." Ohio University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1339520527.
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Romano, Michele. "Near real-time detection and approximate location of pipe bursts and other events in water distribution systems." Thesis, University of Exeter, 2012. http://hdl.handle.net/10871/9862.
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The research work presented in this thesis describes the development and testing of a new data analysis methodology for the automated near real-time detection and approximate location of pipe bursts and other events which induce similar abnormal pressure/flow variations (e.g., unauthorised consumptions, equipment failures, etc.) in Water Distribution Systems (WDSs). This methodology makes synergistic use of several self-learning Artificial Intelligence (AI) and statistical/geostatistical techniques for the analysis of the stream of data (i.e., signals) collected and communicated on-line by the hydraulic sensors deployed in a WDS. These techniques include: (i) wavelets for the de-noising of the recorded pressure/flow signals, (ii) Artificial Neural Networks (ANNs) for the short-term forecasting of future pressure/flow signal values, (iii) Evolutionary Algorithms (EAs) for the selection of optimal ANN input structure and parameters sets, (iv) Statistical Process Control (SPC) techniques for the short and long term analysis of the burst/other event-induced pressure/flow variations, (v) Bayesian Inference Systems (BISs) for inferring the probability of a burst/other event occurrence and raising the detection alarms, and (vi) geostatistical techniques for determining the approximate location of a detected burst/other event. The results of applying the new methodology to the pressure/flow data from several District Metered Areas (DMAs) in the United Kingdom (UK) with real-life bursts/other events and simulated (i.e., engineered) burst events are also reported in this thesis. The results obtained illustrate that the developed methodology allowed detecting the aforementioned events in a fast and reliable manner and also successfully determining their approximate location within a DMA. The results obtained additionally show the potential of the methodology presented here to yield substantial improvements to the state-of-the-art in near real-time WDS incident management by enabling the water companies to save water, energy, money, achieve higher levels of operational efficiency and improve their customer service. The new data analysis methodology developed and tested as part of the research work presented in this thesis has been patented (International Application Number: PCT/GB2010/000961).
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Mosher, Stephen Glenn. "Neural Network Applications in Seismology." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42329.
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Neural networks are extremely versatile tools, as evidenced by their widespread adoption into many fields in the sciences and beyond, including the geosciences. In seismology neural networks have been primarily used to automatically detect and discriminate seismic signals within time-series data, as well as provide location estimates for their sources. However, as neural network research has significantly progressed over the past three decades, so too have its applications in seismology. Such applications now include earthquake early warning systems based on smartphone data collected from large numbers of users, the prediction of peak ground acceleration from earthquake source parameters, the efficient computation of synthetic seismograms, providing probabilistic estimates of solutions to geophysical inverse problems, and many others. This thesis contains three components, each of which explore novel uses of neural networks in seismology. In the first component, a previously established earthquake detection and location method is supplemented with a neural network in order to automate the detection process. The detection procedure is then applied to a large volume of seismic data. In addition to automating the detection process, the neural network removes the need for several user-defined thresholds, subjective criteria otherwise necessary for the method. In the second component, a novel approach is developed for inverting seafloor compliance data recorded by ocean-bottom seismometers for the shallow shear-wave velocity structure of oceanic tectonic plates. The approach makes use of mixture density networks, a type of neural network designed to provide probabilistic estimates of solutions to inverse problems, something that standard neural networks are incapable of. In the final component of this thesis, the mixture density network approach to compliance inversion is applied to a group of ocean-bottom seismometers deployed along the continental shelf of the Cascadia Subduction Zone in order to investigate shelf sediment properties.
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Beaucé, Eric. "Study of the seismicity in the Western Alps by developing and applying an automatic earthquake detection and location Method." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117906.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences, 2018.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 101-104).
We developed a (almost) fully automatic earthquake detection and location method to study seismicity on regional scales based on array-processing techniques. We combined the beam-formed network response with template matched-filtering to enhance detection capabilities. We applied our method to the study of the seismicity of the Western Alps, and we claim that it can be applied in many different contexts to quickly get high quality earthquake catalogs. The study of the seismicity of the Western Alps revealed continuous seismic activity, organized into background and strongly clustered seismicity. We detected 9,018 seismic events from August 2012 to August 2013, outperforming the reference catalog that accounts for 1,698 events in the same period. Comparisons between our catalog and reference catalogs/ studies show that we retrieve well the main features of the region. We also studied source parameter differences between background seismicity earthquakes and clustered seismicity earthquakes. Using spectral ratios of collocated events, we measured the seismic moments Mo and corner frequencies f, for earthquakes detected with a subset of 11 template events. We found that background seismicity earthquakes follow the scaling law ... usually associated with self-similar earthquakes, whereas clustered earthquakes strongly deviate from this scaling law. Our observations show that the corner frequencies exhibit little dependency on the seismic moments, following a scaling law around ... We conclude that, in our study region, the degree of clustering seems to be driven by the rupture mechanism.
by Eric Beaucé.
S.M.
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Putnam, Michael R. "Responding to Dangerous Accidents Among the Elderly: A Fall Detection Device with Zigbee-Based Positioning." DigitalCommons@CalPoly, 2012. https://digitalcommons.calpoly.edu/theses/859.
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The following paper describes a fall detection and activity monitoring system with position detection based on Zigbee transceivers.The main objective is to reduce the time taken for emergency personnel to respond to falls among the elderly. Especially when the victim is unconscious or delirious, position tracking reduces location determination time within a busy hospital or nursing home environment and facilitates immediate treatment. Reduced response times correlate to decreased morbidity and mortality rates. Background is provided on the major wireless network advances currently deployed in a healthcare setting for asset and personnel tracking, etiology of falls, and several methods of detecting falls using sensors and image processing techniques. Data analysis proves that a precise coordinate tracking system was infeasible using the XBee RF module (based on the Zigbee protocol) due to environmental noise, a poor antenna construction and lack of precise signal strength measurements. A primitive scheme with lower resolution and higher reliability associating a single location with each Zigbee transceiver was employed. A pedometer function was added to the project to monitor the user’s daily activity and to potentially serve as a predictor of falls through the interpretation of mobility and gait patterns related to step counts.
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Baxter, Matt. "Damage assessment by Acoustic Emission (AE) during landing gear fatigue testing." Thesis, Cardiff University, 2007. http://orca.cf.ac.uk/54811/.
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Xia, Tao. "Frequency Monitoring Network (FNET) Algorithm Improvements and Application Development." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/77296.
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The Internet Based real-time GPS synchronized wide-area Frequency Monitoring Network (FNET) is an extremely low cost and quickly deployable wide-area frequency measurement system with high dynamic accuracy which consists of Frequency Disturbance Recorder (FDR) distributed to more than 100 places around North America and an Information Management System situated at Virginia Tech. Since its first FDR deployment in 2003, the FNET system has been proved to be able to reliably receive phasor data accurately measured at and instantaneously sent via the Internet from different locations of interest, and efficiently run the analyzing program to detect and record significant system disturbances and subsequently estimate the location of disturbance center, namely the event location, in the electric grid based on the information gathered. The excellent performance of the FNET system so far has made power grid situation awareness and monitoring based on distribution level frequency measurements a reality, and thus advances our understanding of power system dynamics to a higher level and in a broader dimensionality.
Chapter 1 and Chapter 2 of this dissertation briefly introduce the genesis and the architecture of the FNET system, followed by a summary of its concrete implementations. Chapter 3 and Chapter 4 outline FNET frequency estimation algorithm and phase angle estimation algorithm, including their attributes and the new methodologies to enhance them. In Chapter 5, the report discusses the algorithms developed at FNET to detect the frequency disturbance and estimate the disturbance location by the triangulation procedure using real-time frequency data and geographic topology of the FNET units in the power grid where the disturbance occurs. Then, the dissertation proceeds to introduce the FNET angle-based power system oscillation detection and present some research about Matrix Pencil Modal Analysis of FNET phase angle oscillation data in the following two chapters. Lastly, the content of this report is summarized and the future work envisioned in Chapter 8.Ph. D.
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CAI, WEN-HONG, and 蔡旻宏. "Distribution system fault location detection." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/76633038178686425633.
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HUANG, LIANG-KAI, and 黃亮凱. "Circular object detection, location and dimensional measurement." Thesis, 1991. http://ndltd.ncl.edu.tw/handle/28316479835323937223.
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Tsai, Sheng-Da, and 蔡昇達. "SoPC based Automatic Vision Detection and Location System." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/01410371241732891893.
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碩士國立臺灣科技大學
電子工程系
97
Vision Detection and Location System plays an important role in industry. For example, printing house must do precise pattern location to avoid skew. Now many factories measure and locate manually, the drawbacks are time consuming and imprecise. The location system manufacturers have developed automatic vision detection and location system. They combine industry computer, image capture card, IO card and PLC (Programmable logic controller) to achieve the ability of automatic vision detection and location. But this kind of design has some disadvantages, such as high cost and large space. Besides, what the worst is under the dusty and vibrated environment, industry computer is easy to become unstable. Users can’t repair themselves due to the complex system and result in work suspended. We use SoPC development board as the automatic vision detection and location system platform; integrate video input and output module, detection module, location module into a single FPGA chip. In hardware, we propose a high efficient video input and output architecture. In software, we design fast location algorithm and detection algorithm. For industry, using SoPC platform has the advantages of low cost, stable and easy problem removal. The system development platform we use is TERASIC DE2-70 FPGA board. FPGA chip on DE2-70 is Altera Cyclon II EP2C35F896C6N, which provides about 70000 LEs for users. We only need about 8000 LEs to implement our system, so the resource utilization is low.
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CHEN, YUN, and 陳雲. "Fault detection and location of iterative logic array." Thesis, 1990. http://ndltd.ncl.edu.tw/handle/24416569214981023057.
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Chang, Shu-How, and 張書豪. "Multiple Human Face Detection and Location in Classroom." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/42210992934746100688.
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碩士國立臺灣師範大學
資訊工程研究所
98
Face detection and human detection are important in all surveillance method applications. In classroom, we can use detection to assist us to observe student activities. Their response will give some suggestions to teacher, and teacher can improve the teaching. Furthermore, it can extend automatically real-time roll call system to help teacher. We propose a new detection method in classroom. Our method employ a combination of AdaBoost classify faces, applied filter and HOG find trustworthy human face. Bubble-Developing Mechanism (BDM) is a similar object tracking method. It’s an easy way to solve the continuous problem in video sequence or live video. Bubble means individual face results in each of frame and they will have weights just like age. Growth over time, bubbles grow old or die. Because BDM have characteristics of time and continuous, it can enhance the performance of our method. In experiment results, improve AdaBoost and applied filters have a better frame rate than original AdaBoost for real-time face detection. BDM can achieve detection rate from 72% to 94% in single person detection and have average 85% detection rate in multiple people environment.
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Chang, Jui-Sheng, and 張瑞生. "The Study of Location-Aware Fall Detection System." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/7upss3.
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碩士國立陽明大學
醫學工程研究所
97
Recently, the progresses of the microelectronics, wireless communication and embedded system have made the Wireless Sensor Network (WSN) possible. In the hospital, WSN can improve the medical quality by helping medical professionals with monitoring vital signs, position information and activities of patient. In the indoor location technology, IEEE 802.15.4 ZigBee dynamic routing is more popular among wireless sensor network. The advantages of ZigBee are small size, low-cost, low-power consumption, and supporting wireless mesh network standard that make ZigBee suitable in the hospital environment. We propose a location-aware fall detection system that combines falling detection mechanism with ZigBee indoor location engine and sends the location information to the embedded system. When patient falls, medical professionals can rescue the patient immediately that increases the quality of medical care.
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Wang, Jhen-yuan, and 王貞元. "Fire detection and region location in surveillance image." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/77373790782982673723.
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碩士國立臺灣科技大學
電機工程系
96
The fire accident causes economical damage as well as endangering the life of people, so a set of good system of fire detection is necessary. In this thesis, we will combine traditional image process in fire detection and relation of the variation of saturation for flame to deal with fire recognition and fire location. It deals with procedure as follows. First, extraction of the fire pixels in image, and to analyze the region from fire pixels, to label the saturation for fire region by the property of saturation for flame, recognition of fire and orientation of fire location.
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Pin, Chao Shou, and 趙守彬. "Detection and Location Estimation of 802.11 Rogue Devices." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/12026026312139732161.
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Chen, Guan-Chun, and 陳冠均. "The Development of Wearable Location-Aware Fall Detection System." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/50111509869768122206.
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碩士國立陽明大學
醫學工程研究所
98
Fall is the primary cause of accidents for elderly people and often results in serious injury and health threats. It is also the main obstacle of independent living to the frail and elderly people. However, fall management remains a challenge on the improvement of health care quality. A reliable fall-detection system with location-aware functionality provides the user with the reassurance in maintaining an independent lifestyle since the reliable and effective fall detection mechanism and the falling position information will greatly assist urgent medical support and dramatically reduce the cost of medical care. IEEE 802.15.4 ZigBee is the most popular wireless sensor network (WSN) technology for the benefits of dynamic routing, small size, low-cost, low-power consumption, supporting wireless mesh network standard that make ZigBee suitable in the healthcare environment. In this study, we proposed a location-aware fall detection system that combines fall detection mechanism with ZigBee indoor location engine. A tri-axial accelerometer-based fall detector integrated with wireless ZigBee transmission function is worn onto the waist of the residential elders. Urgent falling alarm and location information will be sent back to the embedded system through WSN while the fall event is detected, and specific care professionals or family members are informed as soon as possible. Adequate care can be delivered to the fallers in the shortest rescuing time. Experimental results demonstrate the effectiveness of proposed scheme with high reliability and sensitivity on fall detection. The system is not only cost effective but also portable that fulfills the requirements of fall detection.
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LIN, TSUNG-HSING, and 林宗星. "Research on Crime Detection by Using Location Technology Information." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/9nrsc6.
Full textAbstract:
碩士開南大學
人文社會學院法律碩士在職專班
107
The advancement of modern science and technology is no longer imaginable and controllable, and the use and abuse of technology is actually a frontier. With the evolution of location technology, not only the combination of mobile communication technology, but also the development of criminal behavior characteristics to be faster, more convenient and concealed, resulting in people's rights and interests are more difficult to reply and prosecute. Therefore, police agencies must constantly improve their own learning and detection techniques in order to have sufficient ability to compete with the perpetrators. Problems with the implementation level are worth exploring. This study is mainly aimed at the emergence of information technology in Taiwan on criminal behavior, mainly to explore relevant literature and practical cases, and to focus on fraud, drug violence and cross-border crimes that are most commonly handled in domestic investigation practice. The main focus is on the application of positioning technology in criminal investigation, and the investigators are facing the ability to hear evidence in litigation. The research found that the criminal investigators’ using location technology in public service succumbed to the restrictions on budget procurement by the public service department, and the dilemma of investigating the legal system. The weakness and powerlessness of investigators in the ability had affected the effectiveness of law and order against crime. The research suggests that the content should consider the substantive justice and procedural justice, and simplify the discussion with the investigation. We hope to provide reference for the future implementation of the judicial level and the policing level.
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"Detection of location shift outliers with ordinal categorical variables." 2000. http://library.cuhk.edu.hk/record=b5890274.
Full textAbstract:
Ng Sau-chun.Thesis (M.Phil.)--Chinese University of Hong Kong, 2000.
Includes bibliographical references (leaves 53-54).
Abstracts in English and Chinese.
Chapter Chapter 1 --- Introduction --- p.1
Chapter Chapter 2 --- The Local Influence Approach --- p.5
Chapter 2.1 --- Review of the local influence approach
Chapter 2.2 --- Recent modification of the approach
Chapter Chapter 3 --- Detection of Outliers --- p.9
Chapter 3.1 --- A measure to identify multivariate outliers
Chapter 3.2 --- Identification of outliers in the presence of ordinal categorical variables
Chapter 3.3 --- Examples
Chapter 3.3.1 --- Example --- p.1
Chapter 3.3.2 --- Example --- p.2
Chapter 3.3.3 --- Example --- p.3
Chapter 3.4 --- Behavior of the measure under different patterns
Chapter 3.5 --- Outlying observations and their influence on the estimate of polychoric correlation
Chapter 3.5.1 --- Example
Chapter 3.5.2 --- The simulation studies
Chapter Chapter 4 --- Influential Cells in A Contingency Table --- p.28
Chapter 4.1 --- The model and its estimation
Chapter 4.2 --- The perturbation of observed frequency
Chapter 4.3 --- Normal curvatures as an influence measures
Chapter 4.4 --- Some numerical results
Chapter 4.4.1 --- 2-Dimensional data examples
Chapter 4.4.2 --- Examples on m-Dimensional data
Chapter Chapter 5 --- Discussion --- p.51
Bibliography
Appendix
48
WANG, CHEN-HSIEN, and 王振賢. "The Directional Location Detection of Flowers by Image Recognition." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/19517639518887067752.
Full text
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Chuang, Chen-Yi, and 莊承益. "A Device-free Location Detection Scheme for Indoor Environment." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/17632561649087349761.
Full textAbstract:
碩士國立交通大學
資訊學院資訊學程
100
Among all the wireless localization techniques, most works require users to carry a device, such as a transmitter or a receiver, on the target object to be localized. The need is to develop a device-free localization system, This paper proposes a statistics-based scheme to locate people, where we monitor the received signal strength (RSS) of the Radio Frequency (RF) system in the background environment to recognize that a person may be located in a certain room. This scheme consists of two phases: training phase and online phase. In the training phase, we assume that the building has been deployed with some Wi-Fi APs and a fix receiver; our scheme will measure the RSS distribution while a person is in a room, or not in a room, as the training patterns. In the online phase, we compare the current RSS distribution against the training patterns to detect which room a person is now in. We believe that our framework can provide a valuable solution for device-free localization. A prototype system is developed to verify the practicability of our framework with real data.
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Lin, Wen-Chang, and 林文章. "Skin Color Detection and Face Location in Different sceneries." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/14829781200713549157.
Full textAbstract:
碩士國立中央大學
資訊工程學系碩士在職專班
97
The objective of this study is to detect human faces in images. Many methods have been proposed to detect skin color and then extract the face regions based on the face features. Actually, the face detection is easy for most human beings, but is difficult for computerized autonomous systems. The hardness comes from the variant of skin color and influence of the weather conditions. In this study, we indifidually consider three different sceneries to detect the human face such that the detection is less influenced by the weather conditions. The three sceneries are cloudy outdoor, sunny outdoor, and indoor environments. In each scenery, we define the skin color ranges based on several color methods. Thenextract all skin pixels, and refine the skin-color regions. Thirdly, we use several region features to delete the non-face regions. At last, we extract the eye and mouth from each candidate skin-color regions to verify the faces. The contribution of this study includes: (i) new color transform concept for extract more accurate skin color. (ii) New formula for eye detection in YCbCr color space. (iii) New formula for mouth detection in YCbCr color space.