M.Ing. (Electrical And Electronic Engineering) / State estimation comprises the estimation of the position and velocity (state) of a target based on the processing of noise-corrupted measurements of its motion. This study views a class of measurement processes where the states are unobservable and cannot be estimated without placing additional constraints on the system. The bearings only target motion problem is taken as being representative of this type of problem. The results of this study indicate that practical state· estimation for systems with unobservable measurement processes is possible with the application of estimation theories and available estimation techniques. Due to the inherent nonlinear geometrical characteristics the problem is classified as a unobservable nonlinear estimation problem. A review of state estimation and estimation techniques is presented. The fundamental bearings only target motion concepts are discussed. A representative selection of bearings only estimators made from the published literature, is evaluated. The evaluation consists of a theoretical analysis and a Monte Carlo simulation of the estimators. Two realistic scenario's are considered. A classification framework is presented which may be useful to practical engineers in selecting suitable estimators. Batch estimators are shown to be more stable and likely to be used in bearings only applications than recursive estimators. The importance of isolating the unobservable states from the observable states by using a modified polar co-ordinate system, is stressed. It is also shown that effective data processing can be achieved by using all available measurements and a maximum likelihood estimator.

Chemical vapor deposition (CVD) is an industrially important process to deposit crystalline and amorphous thin films on solid substrates. In situ sensing for CVD is necessary for process monitoring, fault detection, and process control. The challenge of in situ sensing lies in the prohibitive environment of the CVD process. Optical sensors such as the reflectometer and the ellipsometer are the most promising sensors because they can be installed outside of the deposition chamber, and are sensitive and easy to implement. However, the optical sensors do not measure film properties directly. Mathematical methods are needed to extract film properties from indirect optical measurements. Currently the most commonly used method is least squares fitting. In this project, we systematically investigated in situ reflectometry data interpretation based on state estimation theory. Optical models for light reflection on both smooth and rough surfaces were studied. The model validation results indicated that the effective medium model is better than the scalar scattering model when the surface is microscopically rough. The analysis of the observability for the sensor models indicated that the linearized observability does not always guarantee the true observability of a nonlinear system. We studied various state estimators such as batch least squares fitting (BLS), recursive least squares fitting (RLS), extended Kalman filter (EKF), and moving horizon estimation (MHE). It was shown that MHE is the general least-squares-based state estimation and BLS, RLS, and EKF are special cases of MHE. To reduce the computational requirement of MHE, a modified moving horizon estimator (mMHE) was developed which combines the advantage of the computational efficiency in RLS and the a priori estimate in MHE. State estimators were compared in simulated film growth processes, including both process model mismatch and sensor model mismatch, and reflection of both single wavelength and dual wavelength. In the case of process model mismatch and reflection on a smooth surface, there exists an optimum horizon size for both RLS and mMHE, although mMHE is less sensitive to the horizon size and performs better than RLS at all horizon sizes. The estimate with dual wavelength is more accurate than that with single wavelength indicating that estimation improves with more independent measurements. In the case of reflection on a rough surface, RLS failed to give a reasonable estimate due to the strong correlation between roughness and the extinction coefficient. However, mMHE successfully estimated the extinction coefficient and surface roughness by using the a priori estimate. MHE is much more computationally intensive than mMHE and there is no significant improvement on the estimation results. In the case of sensor model mismatch, either state estimator gave a good result, although mMHE consistently gave a better estimate, especially at a shorter horizon size. In order to test the state estimators in a real world environment, we built a cold-wall low-pressure chemical vapor deposition testbed with an in situ emissivity-correcting pyrometer. Fully automatic data-acquisition and instrument-control software was developed for the CVD testbed using LabVIEW. State estimators were compared using two experimental reflectance data sets acquired under different deposition conditions. The estimated film properties are compared with ex situ ellipsometry and AFM characterization results. In all cases, mMHE consistently yielded better estimates for processes under quite different deposition conditions. This indicated that mMHE is a useful and robust state estimator for in situ sensor data interpretation. By using the information from both the process and the sensor model, one can obtain a better estimate. A good feature of mMHE is that it provides such a versatile framework to organize all these useful information and gives a user the opportunity to interact with fitting and make wise decisions in the in situ sensor data interpretation.

Made available in DSpace on 2018-07-27T17:13:44Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-06-02. Added 1 bitstream(s) on 2018-07-27T17:16:26Z : No. of bitstreams: 1 000888006.pdf: 4113638 bytes, checksum: 7791703042b32cfb18d6779d92b26fb7 (MD5) / O aumento da competitividade entre as empresas têm exigido maiores velocidades de operação e períodos menores de manutenção dos equipamentos, por esse motivo é de suma importância poder estender a vida útil dos equipamentos por meio da predição das possíveis falhas. O objetivo deste projeto é desenvolver uma metodologia que possibilite predizer falhas em componentes de sistemas rotativos. Na simulação numérica os danos são identificadas através da variação no valor RMS do sinal de velocidade do sistema, e a quantificação do dano e feita a partir da minimização da norma do erro entre dados do observador robusto e medidos. Um redutor de engrenagens é projetado a fim de validar o método, foi construído o modelo e identificados os parâmetros desconhecidos, com a utilização dos observadores de estado todos os graus de liberdade foram estimados, e um banco de valores RMS foi desenvolvido para servir de base de comparação. A inclusão de um dano no sistema, através dos valores base, foi possível identificar o dano e com o uso do observador robusto quantificar e localizar o dano no sistema mesmo na presença de ruídos / The increased competition among companies have demanded higher operating speeds and shorter periods of maintenance of equipment, for this reason it is extremely important to be able to extend equipment life through the prediction of potential failures . The objective of this project is to develop a methodology that enables to predict component failures of rotating systems. In numerical simulation, failures are identified by varying the RMS value of the velocity signal system, and quantification of failure made from the minimization of the norm the error between the data measured and robust observer. A gear reducer is designed to validate the method, the model was constructed and identified the unknown parameters, with the use of state observers the degrees of freedom were estimated, and a database RMS values, without fail, was developed to serve as a basis for comparison. With the inclusion of damage to the system through the base values, it was possible to identify the damage and the use of robust observer to quantify and locate the damage in the system even in the presence of noise

Orientador: Gilberto Pechoto de Melo / Banca: Vicente Lopes Junior / Banca: Kátia Luchese Cavalca Dedini / Resumo: O aumento da competitividade entre as empresas têm exigido maiores velocidades de operação e períodos menores de manutenção dos equipamentos, por esse motivo é de suma importância poder estender a vida útil dos equipamentos por meio da predição das possíveis falhas. O objetivo deste projeto é desenvolver uma metodologia que possibilite predizer falhas em componentes de sistemas rotativos. Na simulação numérica os danos são identificadas através da variação no valor RMS do sinal de velocidade do sistema, e a quantificação do dano e feita a partir da minimização da norma do erro entre dados do observador robusto e medidos. Um redutor de engrenagens é projetado a fim de validar o método, foi construído o modelo e identificados os parâmetros desconhecidos, com a utilização dos observadores de estado todos os graus de liberdade foram estimados, e um banco de valores RMS foi desenvolvido para servir de base de comparação. A inclusão de um dano no sistema, através dos valores base, foi possível identificar o dano e com o uso do observador robusto quantificar e localizar o dano no sistema mesmo na presença de ruídos / Abstract: The increased competition among companies have demanded higher operating speeds and shorter periods of maintenance of equipment, for this reason it is extremely important to be able to extend equipment life through the prediction of potential failures . The objective of this project is to develop a methodology that enables to predict component failures of rotating systems. In numerical simulation, failures are identified by varying the RMS value of the velocity signal system, and quantification of failure made from the minimization of the norm the error between the data measured and robust observer. A gear reducer is designed to validate the method, the model was constructed and identified the unknown parameters, with the use of state observers the degrees of freedom were estimated, and a database RMS values, without fail, was developed to serve as a basis for comparison. With the inclusion of damage to the system through the base values, it was possible to identify the damage and the use of robust observer to quantify and locate the damage in the system even in the presence of noise / Mestre