Vehicle navigation systems incorporate on-board sensors/signal receivers and provide necessary positioning and guidance information for land, marine, airborne and space vehicles. Among different navigation solutions, the Global Positioning System (GPS) and an Inertial Navigation System (INS) are two basic navigation systems. Due to their complementary characters in many aspects, a GPS/INS integrated navigation system has been a hot research topic in recent decades. Both advantages and disadvantages of each individual system and their combination are analysed in this thesis. The Micro Electrical Mechanical Sensors (MEMS) successfully solved the problems of price, size and weight with traditional INS, and hence are widely applied in GPS/INS integrated systems. The main problem of MEMS is the large sensor errors, which rapidly degrade the navigation performance in an exponential speed. By means of different methods, such as autoregressive model, Gauss-Markov process, Power Spectral Density and Allan Variance, we analyse the stochastic errors within the MEMS sensors. The test results show that different methods give similar estimates of stochastic error sources. An equivalent model of coloured noise components (random walk, bias instability and ramp noise) is given. Three levels of GPS/IMU integration structures, i.e. loose, tight and ultra-tight GPS/IMU navigation, are introduced with a brief analysis of each character. The loose integration principles are presented with detailed equations as well as the INS navigation principles. The Extended Kalman Filter (EKF) is introduced as the data fusion algorithm, which is the core of the whole navigation system. Based on the system model, we show the propagation of position standard errors with the tight integration structure under different scenarios. Even less than 4 observable GNSS satellites can contribute to the integrated system, especially for the orientation errors. A real test with loose integration is carried out, and the EKF performance is analysed in detail. Since the GPS receivers are normally working with a digital map, the map matching principle and its link-choosing problem are briefly introduced. This problem is proposed to be solved by the lane detection from real-time images. The procedures for the lane detection based on image processing are presented. The test on high ways, city streets and pathways are successfully carried out, and analyses with possible solutions are given for some special failure situations. To solve the large error drift of the IMU, we propose to support the IMU orientation with camera motion estimation from image pairs. First the estimation theory and computer vision principles are briefly introduced. Then both point and line matches algorithms are given. Finally the L1-norm estimator with balanced adjustment is proposed to deal with possible mismatches (outliers). Tests and comparisons with the RANSAC algorithm are also presented. For the latest trend of MEMS chip sensors, their industry and market are introduced. To evaluate the MEMS navigation performance, we augment the EKF with an equivalent coloured noise model, and the basic observability analysis is given. A realistic simulated navigation test is carried out with single and multiple MEMS sensors, and a sensor array of 5-10 sensors are recommended according to the test results and analysis. Finally some suggestions for future research are proposed. / <p>QC 20131016</p>

Made available in DSpace on 2014-06-12T17:40:46Z (GMT). No. of bitstreams: 2 arquivo723_1.pdf: 2509449 bytes, checksum: aee89d3fd6cd28c43ba22ccfaced1689 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2009 / Companhia Hidro Elétrica do São Francisco / Esta dissertação enfoca a questão do erro humano nas atividades relacionadas com a manutenção dos equipamentos de proteção e automação numa grande empresa de transmissão de energia elétrica. A ênfase é no erro humano que tenha provocado o desligamento acidental de alguma função de transmissão. A justificativa do estudo cita ações preventivas aos erros humanos na manutenção, apresenta dados básicos de desligamentos, resume os cenários antes e depois da resolução normativa que alterou a remuneração do setor de transmissão, ressalta os impactos econômicos com a nova regulamentação e aborda aspectos da cultura organizacional. A pesquisa sobre as causas de acidentes no trabalho resume teorias com ênfase no homem (da fadiga; da propensão para acidentes, do puro acaso) e teorias com visão sistêmica (modelos Skill-Rule-Knowledge e Generic Error-Modelling System). Aborda ainda aplicações das teorias de análise e classificação de erros humanos que resultaram no modelo Human Factors Analysis and Classification System. Conclui destacando a dificuldade e a necessidade das empresas abandonarem as análises de acidentes com foco nos erros dos homens para considerarem os fatores organizacionais, apresenta fatores psicológicos que levam a buscar culpados e propostas para alcançar excelentes níveis de segurança. O método proposto para a análise e classificação de erros humanos, composto de nove fases, estabelece análise ampla e participativa, apresenta fluxogramas e diagramas de apoio e um processo de validação das recomendações de modo a obter o comprometimento dos responsáveis pela implantação. Apresenta a visão da análise de acidentes no mundo, alerta para o perigo da tendência em supervalorizar o organizacional , insiste que as organizações não podem perder de vista os atos inseguros. Na aplicação é descrita a avaliação da influência da mudança na tecnologia dos equipamentos de proteção e automação em relação aos erros humanos sendo constatado forte efeito sobre a atividade de cálculo e emissão de ajustes dos equipamentos digitais. A conclusão ressalta as bases teóricas do método proposto, destaca os aplausos às empresas que conseguem evitar análises de acidentes com foco excessivo no humano e sugere estudos envolvendo psicologia, engenharia, psiquiatria, estatística, administração e pedagogia

In this thesis, the measurement uncertainty of Coordinate Measuring Machine (CMM) is analysed and software is designed to simulate this. Analysis begins with the inspection of the measurement process and structure of the CMMs. After that, error sources are defined with respect to their effects on the measurement and then an error model is constructed to compensate these effects. In other words, systematic part of geometric, kinematic and thermal errors are compensated with error modelling. Kinematic and geometric error model is specific for the structure of CMM under inspection. Also, a common orthogonal kinematic model is formed and with using the laser error data of the CMM and error maps of the machine volume is obtained. Afterwards, the models are compared with each other by taking the difference and ratio. The definition and compensation of the systematic errors leave the uncertainty of measurements for analysing. Measurement uncertainty consists of the uncompensated systematic errors and random errors. The other aim of the thesis is to quantify these uncertainties with using the different methods and to inspect the success of these methods. Uncertainty budgeting, comparison, statistical evaluation by designing an experiments and simulation methods are examined and applied to the CMM under inspection. In addition, Virtual CMM software is designed to simulate the task specific measurement uncertainty of circle, sphere and plane without using the repeated measurements. Finally, the performance of the software, highly depending on the mathematical modelling of machine volume, is tested by using actual measurements.

Research Doctorate - Doctor of Philosophy (PhD) / Due to the effects of global warming and climate change there is currently intense and growing international interest in suitable modelling methods for relating satellite remotely sensed spectral imagery of vegetated landscapes to the biophysical structural variables in those landscapes across regional, continental or global scales. Of particular interest here is the satellite optical remote sensing of forest foliage cover—measured as foliage projective cover (FPC)—by Landsat ETM+ (Enhanced Thematic Mapper plus) sensor. In the remote sensing literature, different empirical and physical modelling approaches exist for relating remotely sensed imagery to the landscape parameters of interest, each with their own advantages and disadvantages. These approaches, in the main, may be broadly categorised as belonging to one, or a combination of: spectral mixture analysis (SMA) modelling, canopy reflectance modelling, multiple regression (MR) modelling or, spectral vegetation index (SVI) modelling. This thesis uses the SVI approach, partly in comparison to the MR approach. Both the SVI and MR approaches require field-based data to establish the relationship between the biophysical parameter and the spectral index or spectral responses within defined spectral bandwidths. Surrogate measures of the biophysical parameter are sometimes used extensively to establish this relationship and therefore a separate calibration relationship is required.This has inherent problems when the output of one model is substituted into the next and the effects of carry-over of error from one model to the next are not considered. My main goal is therefore to develop a modelling approach that will allow a larger set of one or more surrogate measures to be combined with a smaller set of ‘true’ measures of the biophysical parameter into the one model for establishing the relationship with the SVI and hence the spectral imagery. Success in meeting the goal is the illustration of a working model using real data. In progression towards meeting the goal, two new modelling ideas are developed and synthesised into the creation of an overall modelling framework for estimating FPC from spectral imagery. The modelling framework, which has potential for use in other applications, allows for the incorporation of different types of data including different calibration relationships between variables while avoiding the usual, stepwise approach to the linking of separate relationship models and their variables. One contribution that is new to both remote sensing and statistical modelling practices involves a polar transformation of the principal components of a multi-spectral image of a local reference landscape to produce a set of empirically based, invariant three-dimensional spectral index transformations that have potential for application to the spectral images of different regional landscapes and possibly global landscapes. In particular, the vegetation index from the set has approximate bounded properties that we exploit for modelling of its contribution to residual variation in its relationships with the biophysical variables measured on the ground. The other contribution to statistical modelling practice that has potential for application by a wide range of disciplines is the direct modelling of interdependent relationships between pairs of bounded variates, each considered to have a measurement error structure that can be modelled as though it is similar to sampling variation. Associated with this particular contribution is the development of novel geometric methods to construct approximate prediction bounds and to assist with model interpretations.

The field of modal testing and analysis is currently facing a surge of interest in error modelling. Several errors which occur during testing campaigns are modelled analytically or numerically and propagated to various system coupling and interface reduction routines effectively. This study aims to propagate human errors, like position measurement errors and orientation measurement errors, and random noise-based errors in the measured Frequency Response Functions(FRFs) to the interface reduction algorithm called Virtual Point Transformation(VPT) and later to a substructure coupling method called Frequency-Based Substructuring(FBS). These methods form the cornerstone for Transfer Path Analsysis (TPA). Furthermore, common sources of error like sensor mass loading effect and sensor misalignment have also been investigated. Lastly, a new method to calculate the sensor positions and orientations after a measurement has been devised based on rigid body properties of the system and from the applied force characteristics. The error propagation was performed using a computationally efficient, moment method of the first order and later validated using Monte-Carlo simulations. The results show that the orientation measurement error is the most significant followed by FRF error and position measurement error. The mass loading effect is compensated using the Structural Modification Using Response Functions (SMURF) method and the sensor misalignment is corrected using coordinate transformation. The sensor positions and orientations are accurately estimated from rigid body properties and applied force characteristics; individually using matrix algebra and simultaneously using an optimization-based non-linear least squares solver. / För närvarande ser vi ett ökat intresse för felmodellering inom området modal provning och analys. Flera fel som uppstår under testserier modelleras analytiskt eller numeriskt och propageras effektivt till olika systemkopplings- och gränssnittsreduktionsrutiner. Denna studie syftar till att hantera mänskliga fel, som positionsmätningsfel och orienteringsmätfel, och slumpmässiga brusbaserade fel i de uppmätta frekvensresponsfunktionerna (FRF) till den gränssnittsreduktionsalgoritm, som kallas ”Virtual Point Transformation” (VPT), och senare till en substrukturskopplingsmetod, som kallas FBS (Frequency-Based Substructuring). Dessa metoder utgör hörnstenen för ”Transfer Path Analsysis” (TPA). Dessutom har vanliga felkällor som sensormassbelastningseffekter och felorientering av sensorer undersökts. Slutligen har en ny metod för att beräkna sensorns positioner och riktningar, efter att mätning gjorts, baserat på systemets stelkroppsegenskaper och de applicerade krafterna. Felpropageringen estimerades med en beräkningseffektiv, momentmetod av första ordningen och validerades senare med Monte-Carlo-simuleringar. Resultaten visar att orienteringsmätfelet är den mest signifikanta felkällan följt av FRF-fel och positionsmätningsfel. Massbelastningseffekten kompenseras med hjälp av ”Structural Modification Using Response Functions” (SMURF) -metoden och sensorjusteringen korrigeras med hjälp av koordinatomvandling. Sensorpositionerna och positioner och orientering beräknas exakt från stelkroppsegenskaperna och de applicerade krafterna; individuellt med matrisalgebra och samtidigt med en optimeringsbaserad icke-linjär minsta kvadratlösare.

Hybrid stepper motors are a common type of electric motor used throughout industry thanks to its low-cost, high torque at low speed and open loop positioning capabilities. However, a closed loop control is often required for industrial applications with high precision requirements. The closed loop control can also be used to lower the power consumption of the motor and ensure that stalls are avoided. It is quite common to utilise a large and costly position encoder or resolver to feedback the position signal to the control logic. This thesis has explored the possibility of using a low-cost position sensor based on Hall elements. Additionally, a sensorless estimation algorithm, using only stator winding measurements, has been investigated both as a competitive alternative and as a possible complement to the position sensor. The thesis work summarises and discusses previous research attempts to adequately measure or estimate and control the hybrid stepper motors position and load angle without using a typical encoder or resolver. Qualitative results have been produced through simulations prior to implementation and experimental testing. The readings from the position sensor is subject to noise, owing to its resolution and construction. The position signal has been successfully filtered, improving its accuracy from 0.56° to 0.25°. The output from the sensorless estimation algorithm is subject to non-linear errors caused by errors in phase voltage measurements and processing of velocity changes. However, the dynamics are reliable at constant speeds and could be used for position control.