Biomimetic mems artificial neuromast sensors for fish-like underwater sensing
Evolution bestowed the blind cave fish Astyanax mexicanus fasciatus with a resourcefully designed lateral-line of sensors that enable the fish to swim dexterously and navigate with great agility in hydrodynamically challenging underwater environment. The lateral-line plays a vital role in m...
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DRNTU::Engineering Kottapalli Ajay Girl Prakash Biomimetic mems artificial neuromast sensors for fish-like underwater sensing |
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Evolution bestowed the blind cave fish Astyanax mexicanus fasciatus with a
resourcefully designed lateral-line of sensors that enable the fish to swim dexterously and
navigate with great agility in hydrodynamically challenging underwater environment. The
lateral-line plays a vital role in many tasks performed by the fish, including schooling, object
detection and avoidance, energy-efficient maneuvering, rheotaxis, etc. The lateral-line works
on a 'touch at a distance' sensing principle and enables the blind fish to "see" by imaging
distortions in self-generated flow patterns created due to the presence of an underwater
stimulus (object). The lateral-line of the fish is made of a number of neuromasts which form
the principle sensing elements. Two types of neuromasts in the fish, namely, the superficial
neuromasts (SNs) and the canal neuromasts (CNs), which work by the principle of division of
labour, gratify most of the sensing needs of the blind fish. The SNs, present superficially on
the surface of the skin, act as velocity sensors and the CNs present sub-dermally within a
canal-like structure, act as acceleration sensors. Fundamentally, both these neuromasts
consist of a cupula that extends into the flow, the haircells that generate electric impulses, and
the cupular fibrils that offer mechanical strength to the cupula.
An artificial lateral-line system that replicates the functionality of the lateral-line in
fish would be a great benefit for the navigation of underwater vehicles. An example would be
- flow sensing around the bodies of the vehicles could benefit in achieving energy-efficient
maneuvering and in real-time detection of near-field underwater objects. Researchers
working in the fields of marine navigation are in a constant surge for improving
maneuverability and finding inexpensive, light-weight, power saving alternatives for sensors
on the vehicles which could perform passive sensing. This thesis, for the first time, reports a
complete biomimetic MEMS sensory analogue of the mechanosensory lateral-line developed
using polymer materials. This includes the development both artificial SN and CN sensors that can perform a complete underwater sensmg with abilities that rival those of the
biological neuromasts on the blind cave fish. Liquid crystal polymer (LCP), owing to the
plethora of advantages it offers for sensors for underwater sensing, in particular, is used as
the structural membrane material in the MEMS sensor developed. The two types of haircell
sensors developed in this work - SN inspired LCP haircell sensors, and the CN inspired PZT
haircell sensors, showed excellent performance in sensing steady-state (dc) and oscillatory
flows (ac) underwater respectively. The LCP haircell sensors demonstrate a high sensitivity
of 0.022 m V /(m/s) and a threshold velocity detection limit of 0.015 m/s in sensing dc water
flows. The piezoelectric haircell sensors display a sensitivity 22 m V /(mm/s) and a threshold
velocity detection limit of 8.24 ~m/s for sensing ac flows in water. Translating the knowledge
gained from the morphology of the individual neuromast, we developed artificial cupula
sensors employing Hyaluronic acid-methacrylic anhydride (HA-MA) hydrogel. HA-MA
hydrogel resulted in having the same mechanical and material properties as the biological
cupula of the fish in the nano-indentation and rheology measurements conducted. A
nanofibril scaffold developed by electrospinning process assists the formation of a prolatespheroid
shaped cupula. The addition of the biomimetic cupula enhanced the sensitivity of
the naked haircell sensor manifold times.
However the artificial SN sensors show a good performance, these sensors become
saturated with strong background low frequency flow (noise). In order to detect stimulus
generated disturbances underwater in noisy background flow conditions, artificial canal
versions of the biological CNs are designed and fabricated. A comparative study of the
performance of the artificial CN and the SN sensors is made by testing the sensors in the
presence of both dc and ac flows. The artificial CNs, in comparison with the artificial SNs,
revealed a high immunity to the background noise and act as a good bio-mechanical spectral
filter. |
author2 |
Miao Jianmin |
author_facet |
Miao Jianmin Kottapalli Ajay Girl Prakash |
format |
Theses and Dissertations |
author |
Kottapalli Ajay Girl Prakash |
author_sort |
Kottapalli Ajay Girl Prakash |
title |
Biomimetic mems artificial neuromast sensors for fish-like underwater sensing |
title_short |
Biomimetic mems artificial neuromast sensors for fish-like underwater sensing |
title_full |
Biomimetic mems artificial neuromast sensors for fish-like underwater sensing |
title_fullStr |
Biomimetic mems artificial neuromast sensors for fish-like underwater sensing |
title_full_unstemmed |
Biomimetic mems artificial neuromast sensors for fish-like underwater sensing |
title_sort |
biomimetic mems artificial neuromast sensors for fish-like underwater sensing |
publishDate |
2015 |
url |
http://hdl.handle.net/10356/65091 |
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sg-ntu-dr.10356-650912023-03-11T17:08:47Z Biomimetic mems artificial neuromast sensors for fish-like underwater sensing Kottapalli Ajay Girl Prakash Miao Jianmin School of Mechanical and Aerospace Engineering Singapore-MIT Alliance Programme DRNTU::Engineering Evolution bestowed the blind cave fish Astyanax mexicanus fasciatus with a resourcefully designed lateral-line of sensors that enable the fish to swim dexterously and navigate with great agility in hydrodynamically challenging underwater environment. The lateral-line plays a vital role in many tasks performed by the fish, including schooling, object detection and avoidance, energy-efficient maneuvering, rheotaxis, etc. The lateral-line works on a 'touch at a distance' sensing principle and enables the blind fish to "see" by imaging distortions in self-generated flow patterns created due to the presence of an underwater stimulus (object). The lateral-line of the fish is made of a number of neuromasts which form the principle sensing elements. Two types of neuromasts in the fish, namely, the superficial neuromasts (SNs) and the canal neuromasts (CNs), which work by the principle of division of labour, gratify most of the sensing needs of the blind fish. The SNs, present superficially on the surface of the skin, act as velocity sensors and the CNs present sub-dermally within a canal-like structure, act as acceleration sensors. Fundamentally, both these neuromasts consist of a cupula that extends into the flow, the haircells that generate electric impulses, and the cupular fibrils that offer mechanical strength to the cupula. An artificial lateral-line system that replicates the functionality of the lateral-line in fish would be a great benefit for the navigation of underwater vehicles. An example would be - flow sensing around the bodies of the vehicles could benefit in achieving energy-efficient maneuvering and in real-time detection of near-field underwater objects. Researchers working in the fields of marine navigation are in a constant surge for improving maneuverability and finding inexpensive, light-weight, power saving alternatives for sensors on the vehicles which could perform passive sensing. This thesis, for the first time, reports a complete biomimetic MEMS sensory analogue of the mechanosensory lateral-line developed using polymer materials. This includes the development both artificial SN and CN sensors that can perform a complete underwater sensmg with abilities that rival those of the biological neuromasts on the blind cave fish. Liquid crystal polymer (LCP), owing to the plethora of advantages it offers for sensors for underwater sensing, in particular, is used as the structural membrane material in the MEMS sensor developed. The two types of haircell sensors developed in this work - SN inspired LCP haircell sensors, and the CN inspired PZT haircell sensors, showed excellent performance in sensing steady-state (dc) and oscillatory flows (ac) underwater respectively. The LCP haircell sensors demonstrate a high sensitivity of 0.022 m V /(m/s) and a threshold velocity detection limit of 0.015 m/s in sensing dc water flows. The piezoelectric haircell sensors display a sensitivity 22 m V /(mm/s) and a threshold velocity detection limit of 8.24 ~m/s for sensing ac flows in water. Translating the knowledge gained from the morphology of the individual neuromast, we developed artificial cupula sensors employing Hyaluronic acid-methacrylic anhydride (HA-MA) hydrogel. HA-MA hydrogel resulted in having the same mechanical and material properties as the biological cupula of the fish in the nano-indentation and rheology measurements conducted. A nanofibril scaffold developed by electrospinning process assists the formation of a prolatespheroid shaped cupula. The addition of the biomimetic cupula enhanced the sensitivity of the naked haircell sensor manifold times. However the artificial SN sensors show a good performance, these sensors become saturated with strong background low frequency flow (noise). In order to detect stimulus generated disturbances underwater in noisy background flow conditions, artificial canal versions of the biological CNs are designed and fabricated. A comparative study of the performance of the artificial CN and the SN sensors is made by testing the sensors in the presence of both dc and ac flows. The artificial CNs, in comparison with the artificial SNs, revealed a high immunity to the background noise and act as a good bio-mechanical spectral filter. Doctor of Philosophy (MAE) 2015-06-15T01:37:51Z 2015-06-15T01:37:51Z 2013 2013 Thesis http://hdl.handle.net/10356/65091 en 231 p. application/pdf |