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Energy method for the optimization of a silicon resonant accelerometer

Authors: Jing Zhang; Qin Shi 0002; Yan Su; An Ping Qiu;

Energy method for the optimization of a silicon resonant accelerometer

Abstract

This study investigated the application of energy-consume concept on a silicon resonant accelerometer (SRA) to address design issues. Constrained by micro-fabrication technology, structure of the SRA is formed by resonators, micro-lever mechanisms, proof mass and multi flexures. They are referred to as compliant mechanisms. Based on the energy conservation law, an energy theoretical model on the structure of the sensor has been built and structural parameters were obtained using this novel method. Sensitivity of the structure after optimization has been increased from 127Hz/g to 157.4Hz/g, while the energy transmitted to the force resonators has been increased from 24.33% to nearly 60%. Results of closed-form and tests exhibited in good agreement. The bias stability(1σ) removing the start time was 13.7μg. The sensitivity nolinearity within ± 40g was 136.6ppm. The SRA showed very good properties after optimization. This indicates that this energy-consume method has a good potential on MEMS sensors geometrical design.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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