Micro-Electro-Mechanical Sensors and Actuators

微机电传感器和执行器

• 批准号: RGPIN-2016-04345
• 负责人: AbdelRahman, Eihab
• 金额: $ 2.77万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=615004
• 关键词: Micro; Electro; Mechanical; Sensors; Actuators

My research area is the dynamics of electromechanical systems. The recent availability of Micro-Electro-Mechanical Systems (MEMS) fabrication technology has allowed this field to combine an active research and innovation area to low-cost fabrication. I will exploit this opportunity to introduce novel sensors, actuators, and micro-power generators (MPGs) that outperform their macro counterparts and add new functionality. Towards that end, I propose a research program to advance fundamental knowledge and device development as follows: 1) Micro Actuators: We will investigate analytically (using nonlinear dynamics tools) and experimentally (using, interferometric measurements and analog control) the dynamics of electrostatic, electromagnetic, and hybrid MEMS actuators to understand and stabilize large orbit motions and locate bifurcations in their response. This fundamental research will be deployed to develop hand-held electrostatic MEMS Atomic Force Microscopes (AFM). The AFM will combine technology we have developed and proven for low-voltage actuation, all-electric sub-nano-meter position detection, and feedback control to stabilize long-stroke electrostatic actuators. 2) Micro Sensors: We will use our findings on locations and behavior of electrostatic MEMS in the vicinity of instabilities (bifurcations) to develop bifurcation-based sensors. These sensors exploit an bifurcations to amplify a small stimulus into a large detection signal, thereby improving sensitivity but not cost. We developed a new class of bifurcation sensors: binary sensors that detects whether the concentration of as analyte is above or below a safety threshold. Our static binary sensors demonstrated ability to detect 5ppm of ethanol vapor, one order-of-magnitude better than the commercial equivalent. Binary sensors are also more robust (simpler) than the commercial equivalents. We will develop the fundamental knowledge necessary to design and we will demonstrate dynamic binary gas and chemical (under water) sensors. Exploiting dynamic amplification will improve the sensitivity of dynamic binary sensors by 1-2 orders-of-magnitude over static binary senors. 3) MPGs: We will extend the use of impact oscillators and springless harvester architecture from electromagnetic to electrostatic MPGs and develop wideband and low-frequency electrostatic MPGs. Towards that goal, we will extend our fundamental analysis of MPGs dynamics from electromagnetic to electrostatic transduction. Because electrostatic MPGs become more efficient as their size scales down, we will use them to design electrostatic MEMS MPGs, thereby harvesting low-amplitude motions. Finally, we will combine our expertise in sensors and MPGs to develop passive fatigue sensors that use low-amplitude MPGs as an integrating sensor to measure the total strain energy applied to a structure or kinetic energy spent by a human.

我的研究区域是机电系统的动力学。微型机电系统（MEMS）制造技术的最新可用性使该领域可以将积极的研究和创新区域结合到低成本制造。我将利用这个机会来引入新颖的传感器，执行器和微功率发电机（MPG），以优于其宏对应物并添加新功能。为此，我提出了一项研究计划，以提高基本知识和设备的开发，如下所示： 1）微执行器： 我们将通过分析（使用非线性动力学工具）和实验（使用，干涉测量和模拟控制）进行分析研究，静电，电磁和混合MEMS执行器的动力学以理解和稳定大轨道运动，并在其响应中确定分叉的响应。这项基本研究将被部署以开发手持静电MEMS原子力显微镜（AFM）。 AFM将结合我们开发的技术，并证明用于低压致动，全电动亚纳米级位置检测和反馈控制以稳定长冲程静电执行器。 2）微传感器： 我们将在不稳定性（分叉）附近的静电内存位置和行为上使用我们的发现来开发基于分叉的传感器。这些传感器利用分叉将小刺激放大到大检测信号中，从而提高灵敏度，但不能提高成本。我们开发了一类新的分叉传感器：二元传感器，该传感器检测到AS分析物的浓度是否高于或低于安全阈值。我们的静态二进制传感器表现出检测5ppm乙醇蒸气的能力，比商业同等含量更好。二元传感器也比商业当量更强大（简单）。我们将开发设计必要的基本知识，并将展示动态的二元气体和化学（在水）传感器下。利用动态放大将使动态二进制传感器的灵敏度通过静态二元传感器的1-2级质量提高。 3）MPG： 我们将将冲击振荡器和无弹性收割机结构从电磁扩展到静电MPG，并发展宽带和低频静电MPG。为了实现这一目标，我们将将MPG动力学的基本分析从电磁转移到静电转导。由于静电MPG随着尺寸的缩小而变得更加有效，因此我们将使用它们来设计静电MEMS MPG，从而收获低振幅运动。最后，我们将在传感器和MPG方面结合我们的专业知识，以开发使用低振幅MPG作为集成传感器的被动疲劳传感器，以测量用于人类花费的结构或动能的总应变能。