A laser-based automated mechanical mobility measurement system has been developed that can obtain a very high spatial resolution of frequency response functions (FRFs) for experimental modal analysis where one-dimensional structural motion predominates. With this system FRFs are measured and recorded in a format that is readily imported into a popular modal analysis software. A scanning laser Doppler velocimeter is coupled to a multi-channel FFf analyzer system for efficient data collection and management of spatially distributed FRFs. The objectives in designing this measurement system is to take advantage of the laser's non-contacting nature, its high spatial resolution, and its fast point-to-point movement. By using the scanning capabilities of the laser, experimental mobility FRF data can be collected in those structures that have dominant response in one direction at up to 16,000,000 positions. Moreover, the laser does not mass load the structure thus making the structure time invariant unlike "roving" accelerometers. The design and implementation of this automated mechanical mobility measurement system is presented. Instrumentation interfacing and control issues as well as software development issues are addressed in this thesis. Procedures required to implement the laser-based measurement system are presented. The performance of the laser-based system is presented along with an illustrative example of its use on a free-free rectangular plate where the vibration response is primarily in one direction. / Master of Science

Vehicle motion and tire forces have been estimated using extended Kalman filters for many years. The use of extended Kalman filters is primarily motivated by the simultaneous presence of nonlinear dynamics and sensor noise. Two versions of extended Kalman filters are employed in this thesis: one using a deterministic tire-force model and the other using a stochastic tire-force model. Previous literature has focused on linear stochastic tire-force models and on linear deterministic tire-force models. However, it is well known that there exists a nonlinear relationship between slip variables and tire-force variables. For this reason, it is suitable to use a nonlinear deterministic tire-force model for the extended Kalman filter, and this is the novel aspect at this work. The objective of this research is to show the improvement of the extended Kalman filter using a nonlinear deterministic tire-force model in comparison to linear stochastic tire-force model. The simulation model is a seven degree-of-freedom bicycle model that includes vertical suspension dynamics but neglects the roll motion. A comparison between the linear stochastic tire-force model and the nonlinear deterministic tire-force model confirms the expected results. Simulation studies are performed on some illustrative examples obtaining good tracking performance.

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Mainly based on Li Li's Ph. D. dissertation: University of Arizona, Tucson, 2005. / Includes bibliographical references and index.

Mainly based on Li Li's Ph. D. dissertation: University of Arizona, Tucson, 2005. / Includes bibliographical references and index.

Thesis (Ph.D.)--University of Delaware, 2008. / Principal faculty advisors: Chandra Kambhamettu, Dept. of Computer & Information Sciences; and Cathleen A. Geiger, Dept. of Geography. Includes bibliographical references.

Mainly based on Li Li's Ph. D. dissertation: University of Arizona, Tucson, 2005. / Includes bibliographical references and index. Also available in print.

Thesis (M. App. Sc.)--Carleton University, 2004. / Includes bibliographical references (p. 139-144). Also available in electronic format on the Internet.

Mainly based on Li Li's Ph. D. dissertation: University of Arizona, Tucson, 2005. / Includes bibliographical references and index.

Mainly based on Li Li's Ph. D. dissertation: University of Arizona, Tucson, 2005. / Includes bibliographical references and index. Also available in print.