Collaborative Research: Fish-Inspired Ultra-Sensitive Infrasound Sensor for Critical Infrastructure Monitoring and Geo-hazards Early Warning

合作研究：受鱼类启发的超灵敏次声传感器，用于关键基础设施监测和地质灾害预警

• 批准号: 1031414
• 负责人: Yunfeng Zhang
• 金额: $ 12.5万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1031414&HistoricalAwards=false
• 关键词: Collaborative; Research; Fish; Inspired; Ultra

The objective of this research is to develop an ultra-sensitive infrasound motion sensor with nonlinear adaptive gain, which has potential applications in detecting early warning signals of imminent geo-hazardous events such as landslides. The sensing principle of this infrasound sensor gains inspiration from the ultra-sensitivity of the auditory system of certain fish species in detecting infrasound signals. The core sensing element of this infrasound sensor is a micro-electro-mechanical-system based artificial hair cell, which implements the active amplification and adaptation mechanisms of biological hair cells. Sensor design will be guided with insights made from quantitative modeling and simulation of a fish's hearing sensitivity and selectivity in infrasonic range. A fundamental understanding of how fish sense and process infrasound signals in its auditory system will be achieved through synergistic efforts among this cross-disciplinary project team and strong interactions between the multiple disciplines ranging from fish neuro-anatomy and imaging, nonlinear dynamics modeling, to microelectronics device fabrication and characterization. The outcome of this inter-disciplinary research will lead to new advancements in smart sensor, marine bio-acoustics and geo-hazard mitigation technologies.

本研究的目的是开发一种具有非线性自适应增益的超灵敏次声运动传感器，该传感器在检测即将发生的地质灾害事件（如滑坡）的预警信号方面具有潜在的应用前景。这种次声传感器的感测原理从某些鱼类的听觉系统在检测次声信号时的超灵敏度获得灵感。该次声传感器的核心传感元件是基于微机电系统的人工毛细胞，它实现了生物毛细胞的主动放大和适应机制。传感器的设计将指导从定量建模和模拟鱼的听觉灵敏度和选择性在次声范围内的见解。通过这个跨学科项目团队之间的协同努力以及从鱼类神经解剖学和成像，非线性动力学建模到微电子器件制造和表征等多个学科之间的强大互动，将从根本上了解鱼类如何在其听觉系统中感知和处理次声信号。 这项跨学科研究的成果将导致智能传感器，海洋生物声学和地质灾害缓解技术的新进展。