The diploma thesis is focused on design of an electronic unit for data acquisition of vehicle dynamics. It deals with not only design, but also with the testing and comparing to the other common used electronic units. It also includes proposition for choosing the measured quantities as well as their brief features and description of common used sensors to measure them.

The thesis is focused on digital forensic analysis in operating system Windows. The purpose of this thesis is to provide a preview to the techniques and procedures forensics analysis. There are disclosed available software tools used during forensic analysis. The part of this thesis is also practical process of forensic analysis and developing forensic report

Orientador: Saulo Philipe Sebastião Guerra / Resumo: Este trabalho teve como objetivo avaliar o comportamento dos briquetes durante a queima, considerando a possibilidade de se aprimorar o índice de combustão de briquetes de biomassa (aqui denominado ICOMa) com o uso de um aplicativo de computador, de forma que esta nova proposta fosse mais sensível às variações dos dados que o ICOM (já existente na literatura), bem como determinar sua taxa de perda de massa em função do tempo de queima. Com esta nova proposta, também era esperado que se percebesse uma correlação entre o ICOMa e o poder calorífico superior da biomassa ensaiada, possibilitando estimar esta grandeza, ainda que de forma aproximada, sem o uso de uma bomba calorimétrica. A fabricação do dispositivo para obtenção do ICOMa foi baseada em trabalhos prévios obtidos na literatura, usando uma balança com porta de comunicação em protocolo RS 232, um termopar tipo K para medição da temperatura e um dispositivo para aquisição automática dos dados, feita por um aplicativo computacional também desenvolvido neste trabalho. Os briquetes usados nos ensaios foram de casca de algodão, toco de eucalipto, bagaço de cana-de-açúcar e madeira de pinus, e foram produzidos especificamente para a determinação do ICOMa. O aplicativo atendeu às necessidades do ensaio para obtenção das variáveis relacionadas aos índices de combustão. O ICOMa foi mais sensível que o ICOM na observação da relação entre consumo de massa e geração de calor, e permitiu observar diferenças estatisticamente signific... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: This work aimed to evaluate the behavior of briquettes during burning, considering the possibility of improving the combustion index of biomass briquettes (here called ICOMa) using a software, so that this new proposal to be more sensitive to data variations than ICOM (already existing in the literature), as well as to determine its mass loss rate as a function of burning time. It was also expected with this new proposal, that a correlation between the ICOMa and the higher heating value of the tested biomass could be perceived, making it possible to estimate this magnitude, albeit approximately, without the use of a bomb calorimeter. The manufacture of the device for obtaining the ICOMa was based on previous work obtained in the literature, using a RS 232 communication port scale, a type K thermocouple for temperature measurement, and a device for automatic data acquisition by a computational application, this one developed in this work. The briquettes used in the tests were cotton bark, eucalyptus stump, sugarcane bagasse, and pinewood, and produced specially for the determination of ICOMa. The computational application met the needs of the test to obtain the variables related to the combustion indexes. The ICOMa was more sensitive than the ICOM in observing the relationship between the mass consumption and heat generation, and show a statistical difference between different temperature curves of the materials, unlike the ICOM. The biggest ICOMa found was 0.97 K.h.g-1, and t... (Complete abstract click electronic access below) / Mestre

Indiana University-Purdue University Indianapolis (IUPUI) / Analyzing behaviors of objects on the road is a complex task that requires data from various sensors and their fusion to recreate the movement of objects with a high degree of accuracy. A data collection and processing system are thus needed to track the objects accurately in order to make an accurate and clear map of the trajectories of objects relative to various coordinate frame(s) of interest in the map. Detection and tracking moving objects (DATMO) and Simultaneous localization and mapping (SLAM) are the tasks that needs to be achieved in conjunction to create a clear map of the road comprising of the moving and static objects. These computational problems are commonly solved and used to aid scenario reconstruction for the objects of interest. The tracking of objects can be done in various ways, utilizing sensors such as monocular or stereo cameras, Light Detection and Ranging (LIDAR) sensors as well as Inertial Navigation systems (INS) systems. One relatively common method for solving DATMO and SLAM involves utilizing a 3D LIDAR with multiple monocular cameras in conjunction with an inertial measurement unit (IMU) allows for redundancies to maintain object classification and tracking with the help of sensor fusion in cases when sensor specific traditional algorithms prove to be ineffectual when either sensor falls short due to their limitations. The usage of the IMU and sensor fusion methods relatively eliminates the need for having an expensive INS rig. Fusion of these sensors allows for more effectual tracking to utilize the maximum potential of each sensor while allowing for methods to increase perceptional accuracy. The focus of this thesis will be the dock-less e-scooter and the primary goal will be to track its movements effectively and accurately with respect to cars on the road and the world. Since it is relatively more common to observe a car on the road than e-scooters, we propose a data collection system that can be built on top of an e-scooter and an offline processing pipeline that can be used to collect data in order to understand the behaviors of the e-scooters themselves. In this thesis, we plan to explore a data collection system involving a 3D LIDAR sensor and multiple monocular cameras and an IMU on an e-scooter as well as an offline method for processing the data to generate data to aid scenario reconstruction.

No description available.

Flight data recorders (FDRs) play a critical role in determining root causes of aviation mishaps. Some aircraft record limited amounts of information during flight (e.g. T-1A Jayhawk), while others have no FDR on board (B-52 Stratofortress). This study explores the use of image-based flight data acquisition to overcome a lack of available digitally-recorded FDR data. In this work, images of cockpit gauges were unwrapped vertically, and 2-D cross-correlation was performed on each image of the unwrapped gauge versus a template of the unwrapped gauge needle. Points of high correlation between the unwrapped gauge and needle template were used to locate the gauge needle, and interpolation and extrapolation were performed (based on locations of gauge tick marks) to quantify the value to which the gauge needle pointed. Results suggest that image-based flight data acquisition could provide key support to mishap investigations when aircraft lack sufficient FDR data.

In the automotive industry engines are regularly tested and evaluated by running them for a prolonged time under controlled conditions; environmental conditions, engine load, and drive cycle. These tests are performed in an engine test cell; a computer controlled environment with mechanical fittings and sensors to facilitate the testing of an engine. Our goal was to develop a software suite that provides a distributed graphical interface to the data acquisition and control systems of an engine cell. As we found existing systems to be inadequate in providing a distributed interface, we designed and developed a light weight flexible software suite to remotely, over a network, observe and control the parameters in an engine cell. We used the Fast Light Toolkit (FLTK) GUI library, with networking sockets and process threads to establish the software architecture of the engine test system. Through use of process threads, the client architecture divides tasks into network data sending and receiving, local channel synchronization, and interface operation. Networking sockets used in network data sending and receiving facilitate synchronization of each clients' channel storage and host's channel data. The FLTK GUI library produces visual interactive components of the interface for invoking interactions. Distributed interfacing allows display and modification of the engine cell's operation remotely in locations where relocating an engine cell is not feasible. These locations, such as demonstrations to distant clients and meeting rooms, display the current status of the engine cell through its interfaces without requiring migration of the engine cell to the specified rooms. / Thesis / Master of Applied Science (MASc)

Modern radar and signal processing applications require data acquisition systems capable of high-speed analog data reception and processing. These systems need to support sophisticated signal processing algorithms and reliable high-speed interfaces. The objective of this project is to develop a prototype of a state of the art data acquisition system to aid NASA’s Surface Water and Ocean Topography (SWOT) mission. The SWOT mission aims at monitoring water levels of various water bodies to predict and avoid any catastrophic events. The principal instrument is a Ka-band Radar Interferometer (KaRIN) that is used for the measurement of water levels. The collected data need to be digitized and processed using an FPGA based-data acquisition system housed in a satellite. The scope of this project involves the design, implementation and test of a high-speed printed circuit board (PCB) that serves as the prototype data acquisition system. A lot of emphasis is placed on layout design, as the PCB needs to support data rates up to three Giga samples per second. The goal of this research is to provide Jet Propulsion Laboratory (JPL), NASA with a prototype version of the high- speed acquisition system that can be integrated with the KaRIN system in future.

A system was designed, built and tested in order to test the aerodynamic properties of a standard golf ball in a wind tunnel manufactured by ELD, Inc. model 406(B). The system consists of a rotating shaft, on which the golf ball is attached, connected to a two-axis force transducer. Additionally, an automated data acquisition system was built for enhanced precision of measurements. Data for wind speeds up to 160 ft/s and rotational speeds up to 8,600 rpm were obtained and analyzed. The purpose of the designed apparatus was to allow for studies to better understand the lift and drag coefficients of golf balls during their flight. Subsequent to testing, it was found that the force transducer was not adequate to measure the lift and drag coefficients with sufficient accuracy. Several suggestions have been made on how to improve the wind tunnel so that better results might be obtained in the future.

A method for tuning the spring rate and damping rate of a mountain bike suspension based on a data-driven procedure is presented. The design and development of a custom data acquisition system, known as the "MTB DAQ," capable of measuring acceleration data at the front and rear axles of a bike are discussed. These data are input into a model that is used to calculate the vertical acceleration and pitching angular acceleration response of the bike and rider. All geometric and dynamic properties of the bike and rider system are measured and built into the model. The model is tested and validated using image processing techniques. A genetic algorithm is implemented with the model and used to calculate the best spring rate and damping rate of the mountain bike suspension such that the vertical and pitching accelerations of the bike and rider are minimized for a given trail. Testing is done on a variety of different courses and the performance of the bike when tuned to the results of the genetic algorithm is discussed. While more fine tuning of the model is possible, the results show that the genetic algorithm and model accurately predict the best suspension settings for each course necessary to minimize the vertical and pitching accelerations of the bike and rider.