Parametrically excited MEMS vibration energy harvesters with design approaches to overcome the initiation threshold amplitude

Resonant-based vibration harvesters have conventionally relied upon accessing the fundamental mode of directly excited resonance to maximize the conversion efficiency of mechanical-to-electrical power transduction. This paper explores the use of parametric resonance, which unlike the former, the resonant-induced amplitude growth, is not limited by linear damping and wherein can potentially offer higher and broader nonlinear peaks. A numerical model has been constructed to demonstrate the potential improvements over the convention. Despite the promising potential, a damping-dependent initiation threshold amplitude has to be attained prior to accessing this alternative resonant phenomenon. Design approaches have been explored to passively reduce this initiation threshold. Furthermore, three representative MEMS designs were fabricated with both 25 and 10 μm thick device silicon. The devices include electrostatic cantilever-based harvesters, with and without the additional design modification to overcome initiation threshold amplitude. The optimum performance was recorded for the 25 μm thick threshold-aided MEMS prototype with device volume ∼0.147 mm3. When driven at 4.2 ms -2, this prototype demonstrated a peak power output of 10.7 nW at the fundamental mode of resonance and 156 nW at the principal parametric resonance, as well as a 23-fold decrease in initiation threshold over the purely parametric prototype. An approximate doubling of the half-power bandwidth was also observed for the parametrically excited scenario. © 2013 IOP Publishing Ltd.

Analytical model and experimental validation of friction laws for composites under low loads

In order to account for interfacial friction of composite materials, an analytical model based on contact geometry and local friction is proposed. A contact area includes several types of microcontacts depending on reinforcement materials and their shape. A proportion between these areas is defined by in-plane contact geometry. The model applied to a fibre-reinforced composite results in the dependence of friction on surface fibre fraction and local friction coefficients. To validate this analytical model, an experimental study on carbon fibrereinforced epoxy composites under low normal pressure was performed. The effects of fibre volume fraction and fibre orientation were studied, discussed and compared with analytical model results. © Springer Science+Business Media, LLC 2012.

Analytical formulation of modal frequency split in the elliptical mode of SCS micromechanical disk resonators

This paper presents an analytical formulation of frequency splitting observed in the elliptical modes of single crystal silicon (SCS) micromechanical disk resonators. Taking the anisotropic elasticity of SCS into account, new formulae for computing modal mass and modal stiffness are first derived for accurate prediction of the modal frequency. The derived results are in good agreement with finite element simulation, showing a factor of 10 improvement in the prediction accuracy as compared to using the formula for the isotropic case. In addition, the analysis successfully explains the effect of anisotropy on the modal frequency splitting of primary elliptical modes, for which the maximum modal displacement is aligned with the directions of maximum (1 1 0) and minimum (1 0 0) elasticity respectively on a (1 0 0) SCS wafer. The measured frequency splitting of other degenerate modes is due to the manufacturing imperfections. © 2014 IOP Publishing Ltd.

New approaches to materials education

A novel approach to the teaching of material to engineering students is outlined. It starts from the overview of the "world" of materials made possible by material property charts, and develops both an understanding of material properties and skills in selecting materials and processes to meet design specifications. It is supported by extensive computerbased methods and tools, and is well adapted both for elementary and for advanced courses. © 2003 by Granta Design Limited. Published by the American Institute of Aeronautics and Astronautics, Inc.

Synchronization in a coupled architecture of microelectromechanical oscillators

There has been much recent interest in engineering the phenomenon of synchronization in coupled micro-/nano-scale oscillators for applications ranging from precision time and frequency references to new approaches to information processing. This paper presents descriptive modelling detail and further experimental validation of the phenomenon of mutual synchronization in coupled MEMS oscillators building upon recent experimental validation of this concept by the present authors. In particular, the underlying dependence of the observation of synchronization on system parameters is studied through numerical and analytical modelling while considering essential nonlinearities in both the resonator and circuit domain. Experimental results demonstrating synchronized response are elaborated based on the realization of electrically coupled MEMS resonator based square-wave oscillators. The experimental results on frequency entrainment are found to be in general agreement with results obtained through analytical modeling and numerical simulation. The concept presented here is scalable and could be used to investigate the dynamics of large-arrays of coupled MEMS oscillators. © 2014 AIP Publishing LLC.

Single camera pose estimation using Bayesian filtering and Kinect motion priors

Traditional approaches to upper body pose estimation using monocular vision rely on complex body models and a large variety of geometric constraints. We argue that this is not ideal and somewhat inelegant as it results in large processing burdens, and instead attempt to incorporate these constraints through priors obtained directly from training data. A prior distribution covering the probability of a human pose occurring is used to incorporate likely human poses. This distribution is obtained offline, by fitting a Gaussian mixture model to a large dataset of recorded human body poses, tracked using a Kinect sensor. We combine this prior information with a random walk transition model to obtain an upper body model, suitable for use within a recursive Bayesian filtering framework. Our model can be viewed as a mixture of discrete Ornstein-Uhlenbeck processes, in that states behave as random walks, but drift towards a set of typically observed poses. This model is combined with measurements of the human head and hand positions, using recursive Bayesian estimation to incorporate temporal information. Measurements are obtained using face detection and a simple skin colour hand detector, trained using the detected face. The suggested model is designed with analytical tractability in mind and we show that the pose tracking can be Rao-Blackwellised using the mixture Kalman filter, allowing for computational efficiency while still incorporating bio-mechanical properties of the upper body. In addition, the use of the proposed upper body model allows reliable three-dimensional pose estimates to be obtained indirectly for a number of joints that are often difficult to detect using traditional object recognition strategies. Comparisons with Kinect sensor results and the state of the art in 2D pose estimation highlight the efficacy of the proposed approach.