A learning control algorithm is presented that reduces the closing time of a radio-frequency microelectromechanical systems switch by minimizing bounce while maintaining robustness to fabrication variability. The switch consists of a plate supported by folded-beam springs. Electrostatic actuation of the plate causes pull-in with high impact velocities, which are difficult to control due to parameter variations from part to part. A single degree-of-freedom model was utilized to design a simple learning control algorithm that shapes the actuation voltage based on the open/closed state of the switch. Experiments on three different test switches show that after 5-10 iterations, the learning algorithm lands the switch plate with an impact velocity not exceeding 0.20 m/s, eliminating bounce. Simulations show that robustness to parameter variation is directly related to the number of required iterations for the device to learn the input for a bounce-free closure.

This paper presents a novel micro-scale passive-latching mechanical shock sensor with reset capability. The device integrates a compliant bistable mechanism, designed to have a high contact force and low actuation force, with metal-to-metal electrical contacts that provide a means for interrogating the switch state. No electrical power is required during storage or sensing. Electrical power is only required to initialize, reset, self-test, or interrogate the device, allowing the mechanism to be used in low-power and long shelf-life applications. The sensor has a footprint of about 1 mm2, allowing multiple devices to be integrated on a single chip for arrays of acceleration thresholds, redundancy, and/or multiple sense directions. Modeling and experimental results for a few devices with different thresholds in the 100g to 400g range are given. Centrifuge test results show that the accelerations required to toggle the switches are higher than current model predictions. Resonant frequency measurements suggest that the springs may be stiffer than predicted. Hammer-strike tests demonstrate the feasibility of using the devices as sensors for actual mechanical shock events.

Due to the coupling of thermal and mechanical behaviors at small scales, a Campaign 6 project was created to investigate thermomechanical phenomena in microsystems. This report documents experimental measurements conducted under the auspices of this project. Since thermal and mechanical measurements for thermal microactuators were not available for a single microactuator design, a comprehensive suite of thermal and mechanical experimental data was taken and compiled for model validation purposes. Three thermal microactuator designs were selected and fabricated using the SUMMiT V{sup TM} process at Sandia National Laboratories. Thermal and mechanical measurements for the bent-beam polycrystalline silicon thermal microactuators are reported, including displacement, overall actuator electrical resistance, force, temperature profiles along microactuator legs in standard laboratory air pressures and reduced pressures down to 50 mTorr, resonant frequency, out-of-plane displacement, and dynamic displacement response to applied voltages.

This report summarizes design and modeling activities for the MEMS passive shock sensor. It provides a description of past design revisions, including the purposes and major differences between design revisions but with a focus on Revisions 4 through 7 and the work performed in fiscal year 2008 (FY08). This report is a reference for comparing different designs; it summarizes design parameters and analysis results, and identifies test structures. It also highlights some of the changes and or additions to models previously documented [Mitchell et al. 2006, Mitchell et al. 2008] such as the way uncertainty thresholds are analyzed and reported. It also includes dynamic simulation results used to investigate how positioning of hard stops may reduce vibration sensitivity.

A method for identifying a piecewise-linear approximation to the nonlinear forces acting on a system is presented and demonstrated using response data from a micro-cantilever beam. It is based on the Restoring Force Surface (RFS) method by Masri and Caughey, which is very attractive when initially testing a nonlinear system because it does not require the user to postulate a form for the nonlinearity a priori. The piecewise-linear fitting method presented here assures that a continuous piecewise-linear surface is identified, is effective even when the data does not cover the phase plane uniformly, and is more computationally efficient than classical polynomial based methods. A strategy for applying the method in polar form to sinusoidally excited response data is also presented. The method is demonstrated on simulated response data from a cantilever beam with a nonlinear electrostatic force, which highlights some of the differences between the local, piecewise-linear model presented here and polynomial-based models. The proposed methods are then applied to identify the force-state relationship for a micro-cantilever beam, whose response to single frequency excitation, measured with a Laser Doppler Vibrometer, contains a multitude of harmonics. The measurements suggest that an oscillatory nonlinear force acts on the cantilever when its tip velocity is near maximum during each cycle.

A model for computing the force from a gas film squeezed between parallel plates was recently developed using Direct Simulation Monte Carlo simulations in conjunction with the classical Reynolds equation. This paper compares predictions from that model with experimental data. The experimental validation used an almost rectangular MEMS oscillating plate with piezoelectric base excitation. The velocities of the suspended plate and of the substrate were measured with a laser Doppler vibrometer and a microscope. Experimental modal analysis yielded the damping ratio of twelve test structures for several different gas pressures. Small perforation holes in the plates did not alter the squeeze-film damping substantially. These experimental data suggest that the model predicts squeeze-film damping forces accurately. From this comparison, it is seen that these structures have a tangential-velocity accommodation coefficient close to unity.

This paper compares three models for computing forces caused by gas film squeezed between parallel plates. The models are used to calculate damping forces on an oscillating plate at different oscillation frequencies. The damping forces are then used to calculate nondimensional damping ratios. The damping ratios are used in making comparisons among the models and with experimental data. The experiment used an oscillating MEMS plate suspended by folded springs. The substrate (base) was shaken with a piezoelectric transducer. The plate vibrated as a result, especially at the resonant frequency. The velocities of the suspended plate and of the substrate were measured with a laser Doppler vibrometer and a microscope. Experimental modal analysis gave the damping ratio. To achieve a wide range of squeeze numbers, the experiment was repeated under several different pressures. The measurement was also repeated on an array of plates. Experimental data indicate that, for atmospheric and higher pressures, squeeze-film damping forces can be modeled accurately with a very simple model. For lower pressures in the continuum regime, a more complete model by Veijola (2004) predicts the damping ratio very well.

The responses of micro-cantilever beams, with lengths ranging from 100-1500 microns, have been found to exhibit nonlinear dynamic characteristics at very low vibration amplitudes and in near vacuum. This work seeks to find a functional form for the nonlinear forces acting on the beams in order to aide in identifying their cause. In this paper, the restoring force surface method is used to non-parametrically identify the nonlinear forces acting on a 200 micron long beam. The beam response to sinusoidal excitation contains as many as 19 significant harmonics within the measurement bandwidth. The nonlinear forces on the beam are found to be oscillatory and to depend on the beam velocity. A piecewise linear curve is fit to the response in order to more easily compare the restoring forces obtained at various amplitudes. The analysis illustrates the utility of the restoring force surface method on a system with complex and highly nonlinear forces.

Long-term reliability testing of Micro-Electro-Mechanical Systems (MEMS) is important to the acceptance of these devices for critical and high-impact applications. In order to make predictions on aging mechanisms, these validation experiments must be performed in controlled environments. Additionally, because the aging acceleration factors are not understood, the experiments can last for months. This paper describes the design and implementation of a long-term MEMS reliability test bed for accelerated life testing. The system is comprised of a small environmental chamber mounted on an electrodynamic shaker with a laser Doppler vibrometer (LDV) and digital camera for data collection. The humidity and temperature controlled chamber has capacity for 16 MEMS components in a 4x4 array. The shaker is used to dynamically excite the devices using broadband noise, chirp or any other programmed signal via the control software. Driving amplitudes can be varied to maintain the actuation of the test units at the desired level. The actuation is monitored optically via the LDV which can report the displacement or velocity information of the surface. A springmass accelerated aging experiment was started using a controlled environment of 5000 ppmv humidity (roughly 13% at room temperature), temperature of 29 °C, and ±80μm maximum displacement of the mass. During the first phase of the experiment, the resonant frequency was measured every 2 hours. From 114.5 to 450 hours under stress, measurements were taken every 12 hours and after that every 24 hours. Resonant frequency tracking indicates no changes in the structures for 4200 hours of testing.

Structural health monitoring (SHM) is a systematic method for non-destructive evaluation of a structure's performance by sensing, extracting, patterning, and recognizing features of the structural response. Most SHM approaches focus on statistical analysis for damage identification considering only random uncertainties. This article introduces a method that allows accommodating other types of uncertainties due to ambiguity, vagueness, and fuzziness which are statistically non-describable. The proposed method deals primarily with epistemic uncertainty. The method improves damage identification by performing damage pattern recognition using fuzzy sets. In this approach, healthy observations are used to construct a fuzzy set representing healthy performance characteristics. Additionally, the bounds on the similarities among the structural damage states are prescribed. Thus, an optimal group of fuzzy sets representing damage states such as little, moderate, and severe damage can be inferred as an inverse problem from healthy observations only. Piecewise linear functions are used as fuzzy membership functions representing the states of healthy and damaged. The optimal group of damage fuzzy sets is used to classify a set of observations at any unknown state of damage using the principles of fuzzy pattern recognition based on maximum approaching degree. A case study for damage pattern recognition of a model steel bridge is presented and discussed. The approach is capable of identifying damage patterns accurately.

The development and calibration to experimental data of a nonlinear stochastic dynamics model for a Micro-Electro-Mechanical System (MEMS) inertial switch is discussed. The MEMS switch is modeled as a classical vibro-impact dynamic system: a single degree-of-freedom oscillator subject to impact with a single rigid barrier. An applied load, modeled as a stationary Gaussian stochastic process with prescribed power spectral density (PSD), excites the device and causes repetitive impacts with the barrier. A subset of the model parameters are described as correlated random variables to represent the significant unit-to-unit variability observed during testing of a collection of the switches. Experimental measurements from linear modal and nonlinear transient tests on multiple nominally-identical units are used to calibrate the probabilistic model. The calibrated model for the MEMS inertial switch is then used for probabilistic design studies, where the metric of performance is the amount of time the switch remains closed when subject to the applied stochastic load.

We report on experimental work that characterizes the frequency response of resonators of Microfabricated Acoustic Spectrum Analyzer (MASA) devices which were fabricated using Sandia's SUMMiT (TM) processing technology. A 1.1 micron silicon nitride layer was used in the fabrication to isolate the sense mechanism from the actuation mechanism. The devices are actuated using electrostatic vertical comb-drive actuation in a 30-50 mTorr vacuum and the frequency response is measured using a piezo-resistive readout mechanism. Two MASA devices are tested using comb-drive ac signals (e.g., 200mV) superimposed on a dc bias (e.g., 15V). In addition, dc bias voltages placed on the comb-drive are shown to tune the resonant frequency of the resonator. The frequency response of the piezo-resistive readout mechanism is measured using a 10V dc supply voltage supplied across its Wheatstone bridge. The results show that the piezo-resistive readout mechanism can detect resonant behavior and determine resonant frequency. A laser doppler vibrometer is used as an independent means to characterize the frequency response and verify the results.