基于梳齿间距MEMS工艺误差的微传感器电容与静电力分布模型  

Capacitance and Electrostatic Force Distribution Models of Micro Sensors Based on Comb Finger Gaps' MEMS Process Error

作　　者：戴强[1] 于奇[1] 束平[1] 杨洪东[1] 张国俊[1] 

机构地区：[1]电子科技大学,电子薄膜与集成器件国家重点实验室,四川成都610054

出　　处：《仪表技术与传感器》2010年第3期12-14,18,共4页Instrument Technique and Sensor

基　　金：国家自然科学基金项目(60576007)

摘　　要：在理论分析与模拟仿真基础上,提出了由于梳齿微细加工误差所引起的电容和静电力概率分布模型。该模型表明电容和静电力均为类高斯分布,它们在一定区段出现的可能性可根据其准期望和准方差确定,且该准期望与无加工误差情况相比均有小于5%的微小偏移;同时,该准方差依赖于梳齿数目和梳齿加工误差程度,当梳齿数目由10增大到60时,电容与静电力分布准方差分别增大约2倍和1倍,而当梳齿加工误差程度从5%增大到20%时,则分别增大约3.5倍和2.5倍。该模型可望为一大类梳齿结构微传感器或执行器性能偏差的理论研究和工艺实现提供参考。Because the capacitance and electrostatic force are vital to the performance of comb capacitive micro sensors and actuators, based on the comb finger gaps error brought by the MEMS process, the models of capacitance and electrostatic force probability distribution were proposed after theoretical deduction and ANSYS simulation. It is indicated that, by the model, both the capacitance and electrostatic force distributions are quasi-Gaussian distribution type. Hence the probability for the capacitance and electrostatic force occurring in any interval can be estimated by means of quasi-mean and quasi-variance. The quasi-mean is a little bit different from the value of capacitance or electrostatic force without process error, less than 5%. The quasi-variance depends on the comb finger number and process error degree. When the comb finger number increases from 10 to 60, the quasi-variance of capacitance distribution increases 2 times while is about 1 time for electrostatic force distribution and, as process error degree is from 5% to 20%, the quasi-variance increases 1.5 times for capacitance distribution and is about 2.5 times for electrostatic force distribution. The model is helpful for the further performance exploration based on the process error of quite a large class of comb finger micro sensors and actuators.

关 键 词：微传感器 电容分布 静电力分布 概率模型 MEMS工艺误差 

分 类 号：TH82[机械工程—仪器科学与技术] TN401[机械工程—精密仪器及机械]