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.
💡 Analysis
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.
📄 Content
1 Exploiting plume structure to decode gas source distance using metal-oxide gas sensors
Michael Schmuker1,2,3 *, Viktor Bahr2, Ramón Huerta3 1: University of Sussex, School of Engineering and Informatics, Falmer, Brighton BN1 9QJ, UK. 2: Freie Universität Berlin, Dept. of Biology, Chemistry, Pharmacy, Königin-Luise- Str. 1-3, 14195 Berlin, Germany 3: University of California San Diego, BioCircuits Institute, La Jolla, CA 92093- 0328, USA.
- corresponding author
Keywords: Metal-oxide sensors; turbulence; gas plumes; signal processing; source proximity estimation Abbreviations: MOX sensor — Metal-Oxide sensor
PID
— Photo-Ionisation detector
RMSE(CV)
— Root-mean-square error (in cross-validation)
IBI
— Inter-bout intervals
2 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.
3 1 Introduction Estimating the distance of a gas source is important in many scenarios. For example, when monitoring environmental concentrations of certain gases with a stationary sensor, an estimate of the distance to the source of gas emission will help in localising the emission site. Likewise, the success of a robotic agent trying to localise the source of a hazardous gas leak will depend on the speed and accuracy of its estimates of how far upwind the source is. In the biological realm, gas-based navigation plays a crucial role in insects and mammals looking for food and mating partners, or trying to avoid predators. A prime clue to the distance of a gas source is the concentration of the gas. Downwind from the source the gas concentration will decrease through diffusion and the gas plume will be mixed with air by turbulent (advective) processes [1]. If the gas concentration at the source and the wind speed are known, the distance to the source can, in theory, be estimated from the amount of dilution that has taken place while the gas filament has travelled to the site of detection. But this estimation method contains many sources of error, like e.g. an unknown concentration at the source, as in field applications like the localisation of gas leaks or fires. Moreover, in a turbulent environment the measured concentration of a gas released at a remote upwind site highly intermittent [2]. For reliable estimates of gas concentration, measurements have to be averaged over a time interval, prolonging the procedure. Experimental evidence even suggests that in a turbulent, uncontrolled environment, the average concentration is not a very good estimator of source distance, and that the variance of concentration yields better distance estimates [3]. Interestingly, the intermittent nature of a gas plume itself contains information about source distance that is independent of concentration. It has been shown that the rate of concentration fluctuation in a turbulent environment correlates well with the distance to the gas source in the open field [2,4] and in wind-tunnel experiments [5,6]. Generally, fast fluctuations dominate the signal close to the source, while slower components become more prominent further away.
4 These experimental observations were made using photo-ion
This content is AI-processed based on ArXiv data.