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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Modeling and Estimation of Linear and Nonlinear Piezoelectric Systems

Paruchuri, Sai Tej 13 October 2020 (has links)
A bulk of the research on piezoelectric systems in recent years can be classified into two categories, 1) studies of linear piezoelectric oscillator arrays, 2) studies of nonlinear piezoelectric oscillators. This dissertation derives novel linear and nonlinear modeling and estimation methods for such piezoelectric systems. In the first part, this work develops modeling and design methods for Piezoelectric Subordinate Oscillator Arrays (PSOAs) for the wideband vibration attenuation problem. PSOAs offer a straightforward and low mass ratio solution to cancel out the resonant peaks in a host structure's frequency domain. Further, they provide adaptability through shunt tuning, which gives them the ability to recover performance losses because of structural parameter errors. This dissertation studies the derivation of governing equations that result in a closed-form expression for the frequency response function. It also analyzes systematic approaches to assign distributions to the nondimensional parameters in the frequency response function to achieve the desired flat-band frequency response. Finally, the effectiveness of PSOAs under ideal and nonideal conditions are demonstrated in this dissertation through extensive numerical and experimental studies. The concept of performance recovery, introduced in empirical studies, gives a measure of the PSOA's effectiveness in the presence of disorder before and after capacitive tuning. The second part of this dissertation introduces novel modeling and estimation methods for nonlinear piezoelectric oscillators. Traditional modeling techniques require knowledge of the structure as well as the source of nonlinearity. Data-driven modeling techniques used extensively in recent times build approximations. An adaptive estimation method, that uses reproducing kernel Hilbert space (RKHS) embedding methods, can estimate the underlying nonlinear function that governs the system's dynamics. A model built by such a method can overcome some of the limitations of the modeling approaches mentioned above. This dissertation discusses (i) how to construct the RKHS based estimator for the piezoelectric oscillator problem, (ii) how to choose kernel centers for approximating the RKHS, and (iii) derives sufficient conditions for convergence of the function estimate to the actual function. In each of these discussions, numerical studies are used to show the RKHS based adaptive estimator's effectiveness for identifying linearities in piezoelectric oscillators. / Doctor of Philosophy / Piezoelectric materials are materials that generate an electric charge when mechanical stress is applied, and vice versa, in a lossless transformation. Engineers have used piezoelectric materials for a variety of applications, including vibration control and energy harvesting. This dissertation introduces (1) novel methods for vibration attenuation using an array of piezoelectric oscillators, and (2) methods to model and estimate the nonlinear behavior exhibited by piezoelectric materials at very high mechanical forces or electric charges. Arrays of piezoelectric oscillators attached to a host structure are termed piezoelectric subordinate oscillator arrays (PSOAs). With the careful design of PSOAs, we show that we can reduce the vibration of the host structure. This dissertation analyzes methodologies for designing PSOAs and illustrates their vibration attenuation capabilities numerically and experimentally. The numerical and experimental studies also illustrate the robustness of PSOAs. In the second part of this dissertation, we analyze reproducing kernel Hilbert space embedding methods for adaptive estimation of nonlinearities in piezoelectric systems. Kernel methods are extensively used in machine learning, and control theorists have studied adaptive estimation of functions in finite-dimensional spaces. In this work, we adapt kernel methods for adaptive estimation of functions in infinite-dimensional spaces that appear while modeling piezoelectric systems. We derive theorems that ensure convergence of function estimates to the actual function and develop algorithms for careful selection of the kernel basis functions.
2

Modélisation et optimisation d'un récupérateur d'énergie vibratoire électromagnétique non-linéaire multimodale / Modeling and optimization of a multimodal nonlinear electromagnetic vibratory energy recovery

Abed, Issam 09 July 2016 (has links)
Afin d’accomplir les promesses des récupérateurs d’énergie vibratoire (VEHs) qui s’imposent comme unealternative majeure pour garantir l’autonomie des capteurs pour la surveillance, leurs performances en termes debande passante et puissance récupérable doivent être améliorées. Dans cette thèse, à la différence des VEHs classiqueslinéaires et multimodales ou non-linéaires et mono-fréquence, on propose une approche de récupérationd’énergie basée sur des réseaux d’aimants couplés en lévitation ou élastiquement guidés combinant les avantagesdes non-linéarités et des interactions modales. Une étude bibliographique sur les récupérateurs d’énergie vibratoireest effectuée. En particulier, les inconvénients des récupérateurs linéaires et les techniques de réglage de fréquencesont présentées. De plus, les méthodes non-linéaires sont présentées pour définir une procédure de résolution permettantl’étude de la dynamique des récupérateurs non-linéaires. Les équations du mouvement qui contiennentla non-linéarité magnétique, la non-linéarité géométrique et l’amortissement électromagnétique sont résolus enutilisant la méthode de la balance harmonique couplée avec la méthode asymptotique numérique. Une méthodologied’optimisation multi-objectif basée sur l’algorithme Non Sorting Genetic Algorithm est appliquée afin decalculer les solutions optimales pour maximiser les performances du récupérateur d’énergie. Grâce au couplagenon-linéaire et aux interactions modales, pour le cas des trois aimants couplés, l’approche proposée permet la récupérationde l’énergie vibratoire dans la gamme fréquentielle 4;6 - 14;5 Hz, avec une bande passante d’environ190 % et une puissance normalisée de 20,2 mWcm-3g-2. / In order to accomplish the promises of vibration energy harvesters (VEHs) as a major alternative to powersensors, their performances in terms of frequency bandwidth and harvested power have to be improved. In thisthesis, unlike classical VEHs either linear and multimodal or nonlinear and mono-frequency, we propose a vibrationenergy harvesting approach based on arrays of coupled levitated or elastically guided magnets combining thebenefits of nonlinearities and modal interactions.A review of VEHs is carried out. Particularly, the design issues of linear harvesters are addressed and frequencytuning techniques are presented. A review of nonlinear methods is also presented in order to define a solving procedureenabling the investigation of the dynamics of nonlinear VEHs. The equations of motion which include themagnetic nonlinearity, the geometric nonlinearity and the electromagnetic damping are solved using the harmonicbalance method coupled with the asymptotic numerical method. A multi-objective optimization procedure isintroduced and performed using a non-dominated sorting genetic algorithm for the cases of small magnet arraysin order to select the optimal solutions in term of performances by bringing the eigenmodes close to each other interms of frequencies and amplitudes. Thanks to the nonlinear coupling and the modal interactions even for onlythree coupled magnets, the proposed method enable harvesting the vibration energy in the operating frequencyrange of 4.6–14.5 Hz, with a bandwidth of 190 % and a normalized power of 20:2mWcm-3g-2.

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