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Difference between revisions of "Modified Gyroscope"

Line 14: Line 14:
 
Model Order Reduction for parameterized MEMS applications," PhD thesis, Department of Microsystems Engineering,
 
Model Order Reduction for parameterized MEMS applications," PhD thesis, Department of Microsystems Engineering,
 
University of Freiburg, Freiburg, Germany 2007.</ref>. Without applied external rotation, the paddles vibrate in phase
 
University of Freiburg, Freiburg, Germany 2007.</ref>. Without applied external rotation, the paddles vibrate in phase
with the function <math>z(t),</math> see Fig. 1 below. Under the influence of an external rotation about the <math>x</math>-axis (drawn
+
with the function <math>z(t),</math> see <xr id="fig:gyro"/>. Under the influence of an external rotation about the <math>x</math>-axis (drawn
 
in red), an additional force due to the Coriolis acceleration acts upon the
 
in red), an additional force due to the Coriolis acceleration acts upon the
 
paddles. This force leads to an additional small out-of-phase vibration
 
paddles. This force leads to an additional small out-of-phase vibration

Revision as of 09:49, 28 March 2013


Figure 1: Schematic representation of the Gyroscope.

Description

The device is a MEMS gyroscope based on the butterfly gyroscope [1] developed at the Imego institute in Gothenburg, Sweden (see also: http://simulation.uni-freiburg.de/downloads/benchmark/The Butterfly Gyro (35889), where a non-parametrized model for the device is given ). A gyroscope is a device used to measure angular rates in up to three axes.

The basic working principle of the gyroscope can be described as follows, see also [2]. Without applied external rotation, the paddles vibrate in phase with the function z(t), see xx--CrossReference--dft--fig:gyro--xx. Under the influence of an external rotation about the x-axis (drawn in red), an additional force due to the Coriolis acceleration acts upon the paddles. This force leads to an additional small out-of-phase vibration between two paddles on the same side of the bearing. This out-of phase vibration is measured as the difference of the z-displacement of the nodes with the red dots. Thus, measuring the displacement of two adjacent paddles, the rotation velocity can be ascertained.

Motivation

When planning for and making decisions on future improvements of the Butterfly Gyroscope, it is of importance to improve the efficiency of the gyro simulations. Repeated analysis of the sensor structure have to be conducted with respect to a number of important issues. Examples of such are sensitivity to shock, linear and angular vibration sensitivity, reaction to large rates and/or acceleration, different types of excitation load cases and the effect of force-feedback. The use of model order reduction indeed decreases run time for repeated simulations.

The Parametrized Model

Two parameters are of special interest for the model. The first one is the quantity that is to be sensed, the rotation velocity \theta around the x-axes. The second parameter is the width of the bearing, d. The parametrized system below is obtained by finite element discretization of the parametrized model (in the form of partial differential equations) for the gyroscope. The details of constructing the parametrized system can be found in [2]. The system is of the following form:


M(d)\ddot{x}+D(\theta)\dot{x}+T(d)x=B


y=Cx.

Here, M(d)=(M_1+dM_2)\in \mathbb R^{n\times n} is the mass matrix,

D(\theta)=\theta(D_1+dD_2)\in \mathbb R^{n\times n} is the damping matrix,

T(d)=T_1+(1/d)T_2+dT_3\in \mathbb R^{n\times n} is the stiffness matrix,

B \in \mathbb R^{n} is the load vector, C \in \mathbb R^{1 \times n} is the output matrix, x \in \mathbb R^{n} is the state vector, and y \in \mathbb R is the output response.

The variables d and \theta are the parameters of the system, where d is the width of the bearing and \theta is the rotation velocity along the x-axis.

The interesting output y of the system is \delta z(t) which is the difference of the displacement z(t) between the two red dots on the same side of the bearing (see Fig.1). The number of degrees of freedom is n=17913.

The interesting range for the parameters are: \theta\in [10^{-7}, 10^{-5}] and d\in [1,2]. The device works in the frequency range f \in [0.025, 0.25]MHz.

Data

The model is generated in ANSYS. The system matrices M_1, \, M_2, \, D_1, \, D_2, \, T_1, \, T_2, \,T_3, and  B are in the MatrixMarket format (http://math.nist.gov/MatrixMarket/), and can be downloaded here Gyroscope_modi.tgz. The matrix C defines the output, who has zeros at all the entries, except that on the 2315th entry, the value is -1, and on the 5806th entry, the value is 1. In MATLAB notation, it is C(:, 2315)=-1 and C(:, 5806)=1.

References

  1. J. Lienemann, D. Billger, E. B. Rudnyi, A. Greiner, J. G. Korvink, "MEMS Compact Modeling Meets Model Order Reduction: Examples of the Application of Arnoldi Methods to Microsystem Devices," Nanotech, 2004, pp. 303–306.
  2. 2.0 2.1 C. Moosmann, "ParaMOR Model Order Reduction for parameterized MEMS applications," PhD thesis, Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany 2007.

[3] B. Salimbahrami, R. Eid, B. Lohmann, "Model Reduction by Second Order Krylov Subspaces: Extensions, Stability and Proportional Damping," IEEE International Symposium on Intelligent Control, 2006, pp. 2997–3002.

[4] L. Feng, P. Benner, J.G Korvink, "Subspace recycling accelerates the parametric macromodeling of MEMS" International Journal for Numerical Methods in Engineering, to appear.



Contact

Lihong Feng