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This thesis suggests a formulation for updating physically meaningful parameters in analytical finite element(FE) models using scanning laser Doppler vibrometer(SLDV) dynamic response data. The update formulation is demonstrated in several computer simulations. The formulation is the result of incorporating an analytical FE model into an experimental model. The experimental model efficiently utilizes SLDV data to fully exploit the instrument's capability to automatically make measurements at many locations. The data in the experimental model is posed in a manner consistent with an analytical FE model's representation for harmonic response, simplifying comparison between the two. The experimental model, which uses finite element shape functions as a basis for a least squares fit to the data, can be solved to give a velocity field based only on that data. The function resulting from inserting the analytical model into the experimental model is an expression of the prediction error of the FE model as compared to the test data. This function is minimized using a quasi-Newton optimization routine, reducing the error and resulting in an updated model. Computer simulations of the update algorithm indicate that: 1. Analytically supplied derivatives and variable scaling are required by the optimization routine to consistently converge, 2. The percentage error of updated parameters falls within two standard deviations of the data's percentage error, 3. Error in the position of the laser results in the update algorithm's failure, and, 4. Error in the parameters not included in the update will appear as error in the updated parameters' solution. / Master of Science

Bonding composite structures using adhesives offers several advantages over mechanical fastening such as better flow stress, weight saving, improved fatigue resistance and the ability to join dissimilar structures. The hesitation to adopt adhesively bonded composite joints stems from the lack of knowledge regarding damage initiation and propagation mechanisms within the joint. A means of overcoming this hesitation is to continuously monitor damage in the joint. This study proposes a methodology to conduct structural health monitoring (SHM) of an adhesively bonded composite lap joint using acoustic, guided Lamb waves by detecting, locating and predicting the size of damage. Finite element modeling of a joint in both 2D and 3D is used to test the feasibility of the proposed damage triangulation technique. Experimental validation of the methodology is conducted by detecting the presence, location and size of inflicted damage with the use of tuned guided Lamb waves.

Due to a lack of in-situ methods capable of detecting sub-lethal effects of pollutants on soil organisms, many polluted environments are not identified prior to pollution-induced changes in the soil fauna. Therefore, there is a need to develop new non-invasive methods to measure the health of soil organisms. This study aimed to assess to what extent surface borne vibrations can inform about ant health effects from exposure to sublethal doses of a pesticide (imidacloprid). Twelve ant colonies were set up with artificial nests and fed a glucose and imidacloprid solution (0.01 mg/L, 0.1 mg/L, 1 mg/L and 10 mg/L imidacloprid). After two days, five random ants were placed in an arena where the vibrations were recorded in five one-minute blocks using a Laser Doppler Vibrometer (LDV). No significant difference was found in activity per minute between the different concentrations, although there was a measurable increase in mortality between the concentrations from the second day of exposure to the fifth. Even so, the LDV may still be a viable method, as it clearly recorded vibrations caused by ant movement. If more ants were recorded for longer periods, and more replicates were used, it seems likely the method would have been sensitive enough to detect the effect of the studied pesticide. With an improved experiment design, using the LDV for this purpose may be possible, and the current lack of such a method necessitates further research on the subject.

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There are many limitations to the current methods used to measure vibration on rotating structures. These limitations include physical flow blockages, relating the measurement spot to the structure rotation, data processing issues, and having to physically alter the engine. This work further describes aspects of a self-tracking laser vibrometry system that can be used to measure the vibrations of rotating structures. This method, if setup correctly, has the capability to overcome many of the limitations listed above. A study of all misalignment effects is presented in this thesis. The study consists of a parametric sensitivity analysis of misalignment variables, a parametric Monte Carlo analysis of misalignment variables, and a full interaction Monte Carlo analysis of misalignment variables. In addition, the results of the misalignment variable analyses were used to develop a self-tracker test rig for obtaining fan vibration from a Pratt and Whitney JT15D turbofan engine. A prototype this test rig was designed, built, and tested on the turbofan. It was found that in order to achieve acceptable amounts of position and velocity error using the self-tracker LDV system, very strict alignment of the optical equipment is necessary. Additionally, the alignment criteria can likely be achieved with the use of digitally controlled high precision linear motion equipment. / Master of Science

Structural system identification is traditionally related to the estimation of modal parameters (natural frequencies, modal damping ratios, and mode shapes). Various well known modal methods often fail to extract these parameters for heavily damped structures with high modal densities due to the high coupling between densely packed adjacent modes. The recent development of the scanning laser Doppler vibrometer (SLDV) technology that provides efficient and massive dynamic data acquisition with high spatial density makes the new non-modal system identification techniques feasible. The proposed non-modal system identification method is based on the singular value decomposition (SVD) of the spatial mobility matrices that are acquired by the SLDV technique. Data reduction, filtering, periodization, and remapping techniques are applied to the measured data in the spatial domain. Linear and polynomial singular vector interpolation and subspace rotation techniques are applied in the frequency domain for the prediction of the spatial mobility over the frequency range of interest. This non-modal method uses measured frequency response data directly and involves neither curve fitting nor modal parameter extraction. The proposed non-modal technique was applied to a commercial business jet airplane fuselage. The measured mobility data of the fuselage were reduced to a much smaller and very efficient data set that could be easily managed, stored, and retrieved for the reconstruction and/or prediction the dynamic responses of the fuselage in both frequency and spatial domains / Ph. D.