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.
This project aims to develop a bio-inspired infrasound motion (vibration) sensor with adaptive gain and enhanced sensitivity at small excitation level, which potentially can find application in detecting imminent geo-hazardous events such as landslides. The sensing principle of this sensor gains inspiration from the inner ear system of certain fish species and the macula/statolith organ in the statocyst of cephalopod such as octopus. A literature review of hair cell modeling in fish (including cephalopod) hearing system has been conducted. A numerical model comprised of a series of interconnected inverted pendulum with nonlinear links has been established in general finite element softwares – OpenSees and ANSYS. The ANSYS model also features the fluid-structure interaction behavior of the macula statolith organ to simulate the hearing characteristics of the octopus. The dynamic response characteristic of the octopus’s hearing system (statolith and macula) was quantitatively described using the numerical models developed in this project. Hair cell bundle’s active amplification is successfully modeled by establishing newly created tip-link material element to a finite element package – OpenSEES. Understanding the sensing principle of octopus and fishes enables the design of infrasound motion sensor with adaptive gain and enhanced sensitivity, which is very useful for infrastructure monitoring (measuring small rotation angle in buildings and bridges) and landslide detection. As shown in Figure 1, prototype bio-inspired motion sensor that mimics the sensing characteristics of octopus macula-statolith organ was designed, fabricated and tested. This is achieved first by understanding how octopus sense sound (audiogram) through both numerical simulation as well as physiological experiments and characterizing the parameters of the octopus hearing system through dissecting and microscopic imaging. Additionally, in bio-inspired motion sensor design and analysis, the concept of tilt sensing with adaptive gain was also studied, which is based on the correlation of tilt angle with tip deflection of stereocilia hair cell bundle. When it turns, the force at the top mass due to gravity increases in horizontal direction, artificial hair cell bundles deflect accordingly. A small scale landslide simulation experiment was first conducted to explore the feasibility of using tilt sensor for monitoring landslide precursor signal. The outcome of this cross-disciplinary research also helps advancements in marine biology (understanding of hearing characteristics of cephalopods) and bio-inspired sensor technology.
