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Exploiting plume structure to decode gas source distance using metal-oxide gas sensors

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Exploiting plume structure to decode gas source distance using metal-oxide gas sensors. / Schmuker, Michael; Bahr, Viktor; Huerta, Ramón.

In: Sensors and Actuators B: Chemical, Vol. 235, 01.11.2016, p. 636-646.

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@article{77e6a797bf394af38d4f5b8138d98973,
title = "Exploiting plume structure to decode gas source distance using metal-oxide gas sensors",
abstract = "Estimating the distance of a gas source is important in many applications of chemical sensing, like e.g. environmental monitoring, or chemically-guided robot navigation. If an estimation of the gas concentration at the source is available, source proximity can be estimated from the time-averaged gas concentration at the sensing site. However, in turbulent environments, where fast concentration fluctuations dominate, comparably long measurements are required to obtain a reliable estimate. A lesser known feature that can be exploited for distance estimation in a turbulent environment lies in the relationship between source proximity and the temporal variance of the local gas concentration - the farther the source, the more intermittent are gas encounters. However, exploiting this feature requires measurement of changes in gas concentration on a comparably fast time scale, that have up to now only been achieved using photo-ionisation detectors. Here, we demonstrate that by appropriate signal processing, off-the-shelf metal-oxide sensors are capable of extracting rapidly fluctuating features of gas plumes that strongly correlate with source distance. We show that with a straightforward analysis method it is possible to decode events of large, consistent changes in the measured signal, so-called 'bouts'. The frequency of these bouts predicts the distance of a gas source in wind-tunnel experiments with good accuracy. In addition, we found that the variance of bout counts indicates cross-wind offset to the centreline of the gas plume. Our results offer an alternative approach to estimating gas source proximity that is largely independent of gas concentration, using off-the-shelf metal-oxide sensors. The analysis method we employ demands very few computational resources and is suitable for low-power microcontrollers.",
keywords = "Gas plumes, Metal-oxide sensors, Signal processing, Source proximity estimation, Turbulence",
author = "Michael Schmuker and Viktor Bahr and Ram{\'o}n Huerta",
note = "This document is the Accepted Manuscript version of the following article: Michael Schmuker, Viktor Bahr, & Ramon Huerta, {\textquoteleft}Exploiting plume structure to decode gas source distance using metal-oxide gas sensors{\textquoteright}, Sensors and Actuators B: Chemical, Vol. 235: 636-646, November 2016, doi: http://dx.doi.org/10.1016/j.snb.2016.05.098. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. Published by Elsevier. ",
year = "2016",
month = nov,
day = "1",
doi = "10.1016/j.snb.2016.05.098",
language = "English",
volume = "235",
pages = "636--646",
journal = "Sensors and Actuators B: Chemical",
issn = "0925-4005",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Exploiting plume structure to decode gas source distance using metal-oxide gas sensors

AU - Schmuker, Michael

AU - Bahr, Viktor

AU - Huerta, Ramón

N1 - This document is the Accepted Manuscript version of the following article: Michael Schmuker, Viktor Bahr, & Ramon Huerta, ‘Exploiting plume structure to decode gas source distance using metal-oxide gas sensors’, Sensors and Actuators B: Chemical, Vol. 235: 636-646, November 2016, doi: http://dx.doi.org/10.1016/j.snb.2016.05.098. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. Published by Elsevier.

PY - 2016/11/1

Y1 - 2016/11/1

N2 - Estimating the distance of a gas source is important in many applications of chemical sensing, like e.g. environmental monitoring, or chemically-guided robot navigation. If an estimation of the gas concentration at the source is available, source proximity can be estimated from the time-averaged gas concentration at the sensing site. However, in turbulent environments, where fast concentration fluctuations dominate, comparably long measurements are required to obtain a reliable estimate. A lesser known feature that can be exploited for distance estimation in a turbulent environment lies in the relationship between source proximity and the temporal variance of the local gas concentration - the farther the source, the more intermittent are gas encounters. However, exploiting this feature requires measurement of changes in gas concentration on a comparably fast time scale, that have up to now only been achieved using photo-ionisation detectors. Here, we demonstrate that by appropriate signal processing, off-the-shelf metal-oxide sensors are capable of extracting rapidly fluctuating features of gas plumes that strongly correlate with source distance. We show that with a straightforward analysis method it is possible to decode events of large, consistent changes in the measured signal, so-called 'bouts'. The frequency of these bouts predicts the distance of a gas source in wind-tunnel experiments with good accuracy. In addition, we found that the variance of bout counts indicates cross-wind offset to the centreline of the gas plume. Our results offer an alternative approach to estimating gas source proximity that is largely independent of gas concentration, using off-the-shelf metal-oxide sensors. The analysis method we employ demands very few computational resources and is suitable for low-power microcontrollers.

AB - Estimating the distance of a gas source is important in many applications of chemical sensing, like e.g. environmental monitoring, or chemically-guided robot navigation. If an estimation of the gas concentration at the source is available, source proximity can be estimated from the time-averaged gas concentration at the sensing site. However, in turbulent environments, where fast concentration fluctuations dominate, comparably long measurements are required to obtain a reliable estimate. A lesser known feature that can be exploited for distance estimation in a turbulent environment lies in the relationship between source proximity and the temporal variance of the local gas concentration - the farther the source, the more intermittent are gas encounters. However, exploiting this feature requires measurement of changes in gas concentration on a comparably fast time scale, that have up to now only been achieved using photo-ionisation detectors. Here, we demonstrate that by appropriate signal processing, off-the-shelf metal-oxide sensors are capable of extracting rapidly fluctuating features of gas plumes that strongly correlate with source distance. We show that with a straightforward analysis method it is possible to decode events of large, consistent changes in the measured signal, so-called 'bouts'. The frequency of these bouts predicts the distance of a gas source in wind-tunnel experiments with good accuracy. In addition, we found that the variance of bout counts indicates cross-wind offset to the centreline of the gas plume. Our results offer an alternative approach to estimating gas source proximity that is largely independent of gas concentration, using off-the-shelf metal-oxide sensors. The analysis method we employ demands very few computational resources and is suitable for low-power microcontrollers.

KW - Gas plumes

KW - Metal-oxide sensors

KW - Signal processing

KW - Source proximity estimation

KW - Turbulence

UR - http://www.scopus.com/inward/record.url?scp=84973530106&partnerID=8YFLogxK

U2 - 10.1016/j.snb.2016.05.098

DO - 10.1016/j.snb.2016.05.098

M3 - Article

AN - SCOPUS:84973530106

VL - 235

SP - 636

EP - 646

JO - Sensors and Actuators B: Chemical

JF - Sensors and Actuators B: Chemical

SN - 0925-4005

ER -