A flexible liquid crystal polymer MEMS pressure sensor array for fish-like underwater sensing

In order to perform underwater surveillance, autonomous underwater vehicles (AUVs) require flexible, light-weight, reliable and robust sensing systems that are capable of flow sensing and detecting underwater objects. Underwater animals like fish perform a similar task using an efficient and ubiquit...

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Bibliographic Details
Main Authors: Asadnia, M., Triantafyllou, Michael S., Kottapalli, Ajay G. P., Miao, Jianmin, Barbastathis, George
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/97703
http://hdl.handle.net/10220/11946
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Institution: Nanyang Technological University
Language: English
Description
Summary:In order to perform underwater surveillance, autonomous underwater vehicles (AUVs) require flexible, light-weight, reliable and robust sensing systems that are capable of flow sensing and detecting underwater objects. Underwater animals like fish perform a similar task using an efficient and ubiquitous sensory system called a lateral-line constituting of an array of pressure-gradient sensors. We demonstrate here the development of arrays of polymer microelectromechanical systems (MEMS) pressure sensors which are flexible and can be readily mounted on curved surfaces of AUV bodies. An array of ten sensors with a footprint of 60 (L) mm × 25 (W) mm × 0.4 (H) mm is fabricated using liquid crystal polymer (LCP) as the sensing membrane material. The flow sensing and object detection capabilities of the array are illustrated with proof-of-concept experiments conducted in a water tunnel. The sensors demonstrate a pressure sensitivity of 14.3 μV Pa−1. A high resolution of 25 mm s−1 is achieved in water flow sensing. The sensors can passively sense underwater objects by transducing the pressure variations generated underwater by the movement of objects. The experimental results demonstrate the array's ability to detect the velocity of underwater objects towed past by with high accuracy, and an average error of only 2.5%.