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Made available in DSpace on 2014-06-11T19:27:14Z (GMT). No. of bitstreams: 0 Previous issue date: 2006-08-03Bitstream added on 2014-06-13T20:27:41Z : No. of bitstreams: 1 morais_ts_me_ilha.pdf: 1779620 bytes, checksum: b9fc2164652299690dfd01e30502deab (MD5) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Neste trabalho desenvolveram-se metodologias de diagnóstico de falhas utilizando observadores de estado do tipo Filtro de Kalman, nas quais, as entradas para os observadores são identificadas utilizando as funções ortogonais de Fourier, Legendre e Chebyshev. Um tipo de observador denominado Proporcional-Integral é apresentado para a identificação de entradas desconhecidas. Este observador consegue estimar, sob certas condições, as entradas e ou distúrbios presentes no sistema e essas entradas são utilizadas para a diagnose de falha utilizando um observador do tipo Filtro de Kalman. Também é apresentado o desenvolvimento de uma metodologia de identificação de parâmetros bem como das forças de excitação, através das funções ortogonais, utilizando somente a resposta. Apresentam-se resultados obtidos por meio de simulações computacionais e realizados experimentalmente numa bancada de teste pertencente ao laboratório de vibrações mecânicas do Departamento de Engenharia Mecânica de Ilha Solteira. / In this work a methodology for fault diagnosis of mechanical systems was developed by using Kalman Filter state observes, in which the input of the observers are identified by using Fourier, Legendre and Chebyshev orthogonal functions. A proportional-integral observer is presented to the unknown input identification. This observer is able to find the unknown inputs of the system and these inputs are used to fault detection purposes by using a Kalman Filter Observer. The methodology for the identification of system parameters and excitation forces by using only the response of the system, through orthogonal functions. The methodology developed is applied to a mechanical structure containing vibrating tables, in the Mechanical Vibrations Laboratory, at Unesp, Ilha Solteira.

Orientador: Gilberto Pechoto de Melo / Banca: Amarildo Tabone Paschoalini / Banca: Valder Steffen Júnior / Resumo: Neste trabalho desenvolveram-se metodologias de diagnóstico de falhas utilizando observadores de estado do tipo Filtro de Kalman, nas quais, as entradas para os observadores são identificadas utilizando as funções ortogonais de Fourier, Legendre e Chebyshev. Um tipo de observador denominado Proporcional-Integral é apresentado para a identificação de entradas desconhecidas. Este observador consegue estimar, sob certas condições, as entradas e ou distúrbios presentes no sistema e essas entradas são utilizadas para a diagnose de falha utilizando um observador do tipo Filtro de Kalman. Também é apresentado o desenvolvimento de uma metodologia de identificação de parâmetros bem como das forças de excitação, através das funções ortogonais, utilizando somente a resposta. Apresentam-se resultados obtidos por meio de simulações computacionais e realizados experimentalmente numa bancada de teste pertencente ao laboratório de vibrações mecânicas do Departamento de Engenharia Mecânica de Ilha Solteira. / Abstract: In this work a methodology for fault diagnosis of mechanical systems was developed by using Kalman Filter state observes, in which the input of the observers are identified by using Fourier, Legendre and Chebyshev orthogonal functions. A proportional-integral observer is presented to the unknown input identification. This observer is able to find the unknown inputs of the system and these inputs are used to fault detection purposes by using a Kalman Filter Observer. The methodology for the identification of system parameters and excitation forces by using only the response of the system, through orthogonal functions. The methodology developed is applied to a mechanical structure containing vibrating tables, in the Mechanical Vibrations Laboratory, at Unesp, Ilha Solteira. / Mestre

Shape plays an important role in our everyday life to interpret information about the surroundings whether we are aware or not. Together with visual and auditory information, we are able to obtain and process information for different purposes. Output devices such as monitors and speakers convey visual and auditory information while input devices such as touch screen and microphones receive that information for human machine interaction. Such devices have become commonplace but there has yet to be a fitting input/output device utilizing our haptic perception. Digital Clay is a next generation Human Machine Interface (HMI) device for 2.5D shape input/output via an array of hydraulic actuators. This device potentially has wide applications in the areas of engineering, sciences, medicine, military, entertainment etc. The user can perceive the shape of a computer programmed model in a tangible and concrete manner which means an added realism with the addition of the sense of touch. Conversely, the user can also use Digital Clay as an input device to the computer, by shaping and molding desired shapes on the device, no longer limited to drawing models with a mouse on CAD software. Shape display has been achieved with the current 5x5 prototype at the Georgia Institute of Technology but this research seeks to expand its capability to include haptic feedback and consequently shaping mode. This thesis gives an overview of the current 5x5 prototype and implements 2 commonly used haptic control methods, the admittance control and the impedance control. For implementing the admittance control, actuator displacement and velocity controllers and a proportional integral observer (PIO) are designed. The model-based unknown input observer is a solution for force estimation without added sensors in the actuators. For implementing the impedance control, a novel pressure control technique is designed to provide pressure feedback to the actuators array along with accurate and reliable displacement measurement. Both of the haptic control methods are evaluated, hardware and software limitations are outlined and possible future improvements are suggested.

The organic materials used for stator winding insulation are subject to deterioration from thermal, electrical, and mechanical stresses. Stator winding insulation breakdown due to excessive thermal stress is one of the major causes of electric machine failures; therefore, prevention of such a failure is crucial for increasing machine reliability and minimizing financial loss due to motor failure. This work focuses on the development of an efficient and reliable stator winding temperature estimation scheme for small to medium size mains-fed induction machines. The motivation for the stator winding temperature estimation is to develop a sensorless temperature monitoring scheme and provide an accurate temperature estimate that is capable of responding to the changes in the motors cooling capability. A discussion on the two major types of temperature estimation techniques, thermal model-based and parameter-based temperature techniques, reveals that neither method can protect motors without sacrificing the estimation accuracy or motor performance. Based on the evaluation of the advantages and disadvantages of these two types of temperature estimation techniques, a new online stator winding temperature estimation scheme for small to medium size mains-fed induction machines is proposed in this work. The new stator winding temperature estimation scheme is based on a hybrid thermal model. By correlating the rotor temperature with the stator temperature, the hybrid thermal model unifies the thermal model-based and the parameter-based temperature estimation techniques. Experimental results validate the proposed scheme for stator winding temperature monitoring. The entire algorithm is fast, efficient and reliable, making it suitable for implementation in real time stator winding temperature monitoring.