arrow
返回

A parametric analysis based design framework for MEMS g-switch accelerometers

delete2021-02-01
delete4
PRE
AI
M
Murugappan Ramanathan *
N
Nandan Murali
P
Prosenjit Sen
R
Rudra Pratap
DOI:10.1016/j.sna.2020.112423delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
We present an experimentally verified novel design framework for MEMS g-switch acceleration switches. These switches need to engage a physical latch upon sensing a specified threshold acceleration. It is this physical contact between two surfaces under dynamic conditions that introduces nonlinearity in the system response and makes the task of design optimization difficult. We first find analytical solutions for displacement and velocity of the proof mass by linearizing the friction term using a single degree of freedom model and representing the acceleration profile by a Fourier series. We then use these solutions, along with latching constraints on them, to study how the lumped design parameters - mass, suspension spring stiffness, and latching spring stiffness - vary with increasing threshold acceleration. The latching constraints ensure that latching does not occur for any magnitude of acceleration less than the specified threshold value. Subsequently, we build a g-switch model in SIMULINK that uses the variation in design parameters for a given acceleration profile to find an optimal set of values of design parameters for a specified threshold acceleration. We verify our model by fabricating a latch accelerometer using the parameters obtained from this model for a 60g threshold acceleration. A shock input of 60g magnitude and 1.2 ms pulse width is given to the fabricated acceleration switch and the experimental response is recorded using high-speed video images. The analytical response and the experimental response show good agreement. Hence, we believe that this novel design framework can be used to fabricate a latch accelerometer for any arbitrary input shock profile. (C) 2020 Elsevier B.V. All rights reserved.
Keyword:
MEMS g-switch
Shock sensor
Threshold acceleration
Latching beam
Proof mass
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Sensors and Actuators A-Physical 封面图
Sensors and Actuators A-Physical
IF:
4.9
论文数:
1.5W
被引数:
3.3W

机构

I
indian institute of science (iisc) - bangalore
学者数:
1.4W
论文数: 1.4W
被引数: 11
引用论文

引用论文

Aging of the Voice and Swallowing声音与吞咽的老化
err2016-04-22
err0
PREAI
errPaul H. Ward; Ray Colton; Fred McConnell; Leslie Malmgren; Haskins Kashima; Gayle Woodson
err分享
err收藏
err
IF0
err
err0
PREAI
err
err分享
err收藏
Reengineering Clinical Research with Informatics
err2006-09-01
err0
PREAI
errThomas K. Chung; Rita Kukafka; Stephen B. Johnson
err分享
err收藏
err
IF0
err
err0
PREAI
err
err分享
err收藏
学者 查看更多内容