基于MEMS的智能集成汽车传感器的研究

随着汽车传感器的迅速发展和MEMS技术的深入研究,基于MEMS技术的汽车传感器具有广阔的应用前景.本文从传感器原理、MEMS技术理论与制造工艺、智能传感器理论与控制算法、软件与硬件实现、以及集成原理与工艺等几个方面,综合运用MEMS技术、人工智能、信息融合、半导体加工等先进技术,研究基于MEMS技术的智能集成汽车传感器问题.最后对MEMS汽车传感器今后的发展研究进行了探讨.     

Advanced flow measurement and active flow control of aircraft with MEMS

Advanced flow measurement and active flow control need the development of new type devices and systems.Micro-electro-mechanical systems(MEMS) technologies become the important and feasible approach for micro transducers fabrication.This paper introduces research works of MEMS/NEMS Lab in flow measurement sensors and active flow control actuators.Micro sensors include the flexible thermal sensor array,capacitive shear stress sensor and high sensitivity pressure sensor.Micro actuators are the balloon actuator and synthetic jet actuator respectively.Through wind tunnel test,these micro transducers achieve the goals of shear stress and pressure distribution measurement,boundary layer separation control,lift enhancement,etc.And unmanned aerial vehicle(UAV) flight test verifies the ability of maneuver control of micro actuator.In the future work,micro sensor and actuator can be combined into a closed-loop control system to construct aerodynamic smart skin system for aircraft.     

MEMS在控制系统中的应用

微机电系统(MEMS)是一个新兴的跨学科研究领域，借助于MEMS可以实现微观对象的检测与控制以及宏观对象的分布式检测与控制。综述了基于MEMS的主动控制和传感器网络在控制系统中的应用。     

Error analysis and characterization of new MEMS IMU sensors and integration with PPP

Several new MEMS Inertial Measurement Unit(IMU) sensor products have been released recently with improved performance,which have the potential to support much higher precision applications.New MEMS IMUs include the NavChip from InterSense,the Nav440 from Crossbow,the Landmark30/40 from GTI,the SDI500 from Systron Donner.Since they are new in the market,currently there is limited information about their error characterization which however is important for the construction of proper error models for their integration with other sensors such as GPS.This paper will investigate the error characterization of two new MEMS IMU sensors,namely the NavChip and Nav440,using Allan variance technique.In addition to identifying different error terms,different stochastic error modeling methods,such as Gauss-Markov(GM) and Autoregressive(AR) processes,will also be investigated to assess the MEMS IMU sensor biases.Investigation to integrate new MEMS IMU sensors with Precise Point Positioning(PPP) will also be conducted to address the re-convergence issues.     

基于微机电系统洛伦兹平台角速度估计

针对洛伦兹惯性稳定平台对高带宽和高精度角速率需求,提出了基于微机电系统(micro-electro-mechanical system,MEMS)组合传感器的最优速度估计算法.MEMS组合传感器由陀螺仪和加速度计组成,MEMS陀螺仪由于自身特性在速度估计中提供低频速度信息,而加速度计则提供高频信息.最优估计器通过将低频信号与高频信息融合,采用最优控制与估计算法进行速度解算与估计.实验表明,频率在20 Hz内,运动角度在±60°内,MEMS组合传感器速度拟合周期不超过5％,稳定拟合误差不超过7.5％,可以满足平台稳定偏转控制需求.最优状态估计器能在时域与频域上提供无差、高性能的角速度信号.     

Tiny MEMS-Based Pressure Sensors in the Measurement of Intracranial Pressure

This study presents a tiny pressure sensor which is used to measure the Intracranial Pressure （ICP）. The sensor is based on the piezoresistive effect. The piezoresistive pressure sensor is simulated and designed by using nonlinear programming optimizing and Finite Element Analysis （FEA） tools. Two kinds of sensor sizes are designed in the case of childhood and adult. The sensors are fabricated by Microelectro Mechanical Systems （MEMS） process. The test results yield sensitivities of 1.033x 10-2 mV/kPa for the childhood type detection and 1.257x 10-2 mV/kPa for the adult detection with sensor chip sizes of 0.40x0.40 mm2 and 0.50x0.50 mm2, respectively. A novel method for measuring ICP is proposed because of the tiny sizes. Furthermore, relative errors for sensitivity of pressure sensors are limited within 4.76%. Minimum Detectable Pressure （MDP） reaches 128.4 Pa in average.     

石墨烯结构型氨气传感器研究进展

石墨烯基气体传感器具有噪声低、能耗小和常温下即可检测等优点,在医疗诊断、气体检测和农业生产等方面有着广泛的应用。然而,传统石墨烯型传感器往往存在着恢复时间长和选择性低等问题。为了使传感器工作更加灵敏,开发基于石墨烯及其衍生物的复合新型气敏材料用以降低恢复时间和提高选择性,是当前的主要研究热点。简要介绍了近年来石墨烯复合气敏材料（如金属氧化物半导体、导电聚合物、金属有机骨架化合物、二维过渡金属碳氮化物等）用于氨气检测的研究现状,展望了其在微机电系统集成化等领域的应用前景。     

MEMS器件捷联惯导系统旋转调制技术

使用微机电(MEMS)惯性器件利于捷联惯导系统的低成本和小型化,但MEMS器件误差较大.为提高系统精度,引入了一种全自主误差补偿方法——旋转调制.说明了旋转调制对常值误差的抑制作用和对导航精度的改善效果,并在旋转轴数目、旋转方向、旋转连续性和旋转速度等方面比较了不同旋转调制方案.根据MEMS器件的误差特性,选择了一种适合MEMS器件捷联惯导系统的旋转调制方案并自主研发了原理样机.静态和车载实验表明:旋转调制可以明显抑制MEMS器件常值误差对导航精度的影响,200s内俯仰和横滚姿态精度提高了5倍,速度和位置精度提高了近10倍.     

基于 MEMS 辅助的单基线北斗融合测姿算法

载体的姿态信息是导航的重要参数,随着北斗卫星导航系统（Beidou navigation satellite system,BDS）和微机电系统（micro-electro-mechanical systems,MEMS）惯性传感器的发展与完善,高精度、低成本、自主化的融合测姿技术具有广阔的应用前景,因此,提出MEMS辅助单基线北斗融合测姿算法。根据MEMS惯性传感器解算出的姿态信息确定基线向量的搜索范围,从而辅助模糊度函数法（ambiguity function method,AFM）减小整周模糊度搜索空间,提高整周模糊度快速求解的成功率和计算效率。将BDS输出的姿态角信息作为观测信息,对MEMS陀螺仪解算出的姿态信息进行实时校正,实现BDS和MEMS传感器二者的数据融合算法。通过实测数据仿真验证,该算法能够解决信号失锁带来的整周模糊度求解困难的问题,并且测姿系统能在遮挡和动态等复杂环境下提供高质量姿态测量结果。     

基于异构多源传感的行人长航时变步长误差修正技术

低成本微机电系统(micro-electro-mechanical system,MEMS)传感器广泛应用于行人定位导航中,但在长航时下,MEMS传感器零位会随时间产生漂移,导致行人变步长误差成为主要误差.且传统的足绑式导航利用MEMS传感器自身信息判断零速时刻会出现错判漏判等问题.针对这两点,根据行人步态变化规律,在判断零速时刻时,加入压力传感器辅助的异构多源传感,同时针对系统误差设计了用于补偿的误差修正算法.对比传统方法,该设计可以明显提高导航定位精度,定位精度可提高一个数量级.     

声音传感器辐照实验研究

在给定的剂量率点,对动圈式、电容式、硅微式声音传感器进行了大剂量辐照实验研究,观察传感器随总剂量增强时其输出信号的变化,分析辐射效应机理。结果表明：动圈式声音传感器耐辐照性能最强;硅微式声音传感器由于内部放大电路的静态工作点会在γ射线的影响下产生漂移,导致信号输出发生比较严重的失真;电容式声音传感器中用于电磁屏蔽的铝制外壳受到γ射线的影响会产生电荷累积效应,对信号引入较大的噪声。其研究结果对乏燃料后处理系统进行基于声信号的安全状态实时监测提供了支持,是后续故障分析诊断技术的应用的硬件保证。     

基于MEMS的细长体非对称涡控制机理研究

目前,微机电系统（MEMS）作为致动器和传感器已被广泛应用于航空航天领域中。MEMS器件具有很好的功能性、集成性、可控性和鲁棒性等等。根据MEMS器件的特性,采用NS数值计算技术,对细长体在大迎角飞行状态下的非对称涡进行了气动控制。分析了MEMS器件控制流场的机理和将非对称涡转变为对称涡的流场控制机理,获得了MEMS器件控制流场特性的宏观效果。研究表明：MEMS器件对控制大迎角细长旋成体非对称涡和复杂流场具有良好的控制能力。     

薄膜压力传感器的研究进展

物联网产业的发展使传感器的研究得到越来越多的重视。薄膜压力传感器作为传感器的一个重要分支,因其优异的性能得到广泛的使用。简要地介绍了薄膜压力传感器的组成及原理,详细介绍了不同种类材料制成薄膜压力传感器的特点,重点突出了不同合金材料、半导体材料制成的传感器之间性能的差异,并为电阻层材料的选取提供参考意见。通过总结薄膜的制备方法,来阐述在薄膜压力传感器中薄膜的制备技术,总结近年在薄膜制备技术上进行的研究,最后基于近年纳米材料、微电子机械系统（micro-electro-mechanical systems,MEMS）技术、微波技术等技术的发展,结合薄膜压力传感器的研究现状,对其未来的发展进行展望。     

MEMS biomedical implants

The field of micro-electro-mechanical systems(MEMS) has advanced tremendously for the last 20 years.Most commercially noticeably,the field has successfully advanced from pressure sensors to micro physical sensors,such as accelerometers and gyros,for handheld electronics application.In parallel,MEMS has also advanced into micro total analysis system(TAS) and/or lab-on-a-chip applications.This article would discuss a relatively new but promising future direction towards MEMS biomedical implants.Specifically,Parylene C has been explored to be used as a good MEMS implant material and will be discussed in detail.Demonstrated implant devices,such as retinal and spinal cord implants,are presented in this article.     

基于微机电系统传感器的杆塔倾斜度无线监测系统

提出一种新型的基于微机电系统(micro-electro-mechanical system,MEMS)传感器的杆塔倾斜度无线监测系统.硬件设计选用STM32F103CT86为控制器,以BMI160、AK8963为传感器,STM32通过四元数卡尔曼滤波算法对传感器数据进行解算、融合,得到杆塔的倾斜角,通过试验与三轴姿态...     

国际上微型飞行器研究的进展及其关键技术

微型飞行器（MAV）是MEMS传感器和驱动器技术发展的必然产物,同时也是当今先进国家竞相研究的科技前沿课题。该文综述了世界各国对微型飞行器在固定翼、旋翼、扑翼以及微型动力系统方面的研究进展,指出了MAV研究的几项关键技术,并结合我国实际,提出了我国研究MAV的建议。     

无线传感器网络的研究进展

作为下一代“无处不在的计算(Ubiquitous Computing)”形式之一的无线传感器网络,集成了传感器、微机电系统和网络3种技术。目前该领域世界范围内的研究已进入原型机实验阶段与标准制定阶段。就无线传感器网络研究的主要分支、进展及应用进行了综述。     

基于平淡卡尔曼滤波器的微小卫星姿态确定算法

针对扩展卡尔曼滤波（EKF）在线性化过程中会引入误差的问题,采用平淡卡尔曼滤波器（UKF）进行了系统滤波器设计;提出一种构建虚拟观测量的方法,并分析了其噪声特性．虚拟观测量与高精度器件量测量搭配可实现对姿态的校正．以太阳敏感器、微电子机械系统（MEMS）陀螺、磁强计为姿态敏感器件,构建了定姿滤波器并用STK（Satellite Tool Kit）数据进行了仿真．结果表明,所提出方法能有效地提高定姿性能,采用UKF的系统定姿误差与EKF相当,但收敛时间、稳定性要优于EKF．     

Applications of MEMS devices in nanosatellite

micro-electro-mechanical system(MEMS) device has the advantages of both electronic system and mechanical system.With the development of MEMS devices for satellite,it is possible to establish much lighter and smaller nanosatellites with higher performance and longer lifecycle.The power consumption of MEMS devices is usually much lower than that of traditional devices,which will greatly reduce the consumption of power.For its small size and simple architecture,MEMS devices can be easily integrated together and achieve redundancy.Launched on April 18,2004,NS-1 is a nanosatellite for science exploration and MEMS devices test.A mass of science data and images were acquired during its running.NS-1 weights less than 25 kg.It consists of several MEMS devices,including one miniature inertial measurement unit(MIMU),three micro complementary metal oxide semiconductor(CMOS)cameras,one sun sensor,three momentum wheels,and one micro magnetic sensor.By applying micro components based on MEMS technology,NS-1 has made success in the experiments of integrative design,manufacture,and MEMS devices integration.In this paper,some MEMS devices for nanosatellite and picosatellite are introduced,which have been tested on NS-1 nanosatellite or on the ground.     

融合MT2503与MEMS传感器的惯性导航定位算法

为提高惯性导航室内定位算法的精度与连续性,提出一种融合MT2503与MEMS传感器的惯性导航定位算法,算法以MT2503芯片作为定位终端,并将加速度计传感器、陀螺仪,磁力计等传感器与其进行融合,通过加速度计传感器解算步长、步幅、步频,通过陀螺仪与磁力计来识别定位终端微动偏移量,最后在初始位置上累加定位终端位移得出定位终端实时位置。实验证实通过零速修正和卡尔曼滤波对误差进行校正,有效的解决了MEMS(micro-electro mechanical system)定位算法中存在的导航解算误差累积问题,提升了MEMS惯性导航室内定位算法的精度。