Exploiting plume structure to decode gas source distance using metal-oxide gas sensors
Exploiting plume structure to decode gas source distance using metal-oxide gas sensors
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DOI：
10.1016/j.snb.2016.05.098
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发表时间：
2016-11-01
影响因子：
8.4
通讯作者：
Huerta, Ramon
中科院分区：
文献类型：
--
作者：
Schmuker, Michael;Bahr, Viktor;Huerta, Ramon
估计气体源的距离在化学传感的许多应用中是重要的，例如环境监测或化学引导的机器人导航。如果源处的气体浓度的估计是可用的，则源接近度可以从感测部位处的时间平均气体浓度来估计。然而，在湍流环境中，快速浓度波动占主导地位，需要长时间的测量，以获得可靠的估计。在湍流环境中可用于距离估计的一个鲜为人知的特征在于源接近度与局部气体浓度的时间变化之间的关系，源越远，气体相遇的间歇性越大。然而，利用这一特征需要在超快的时间尺度上测量气体浓度的变化，到目前为止，这只能通过使用光电离检测器来实现。在这里，我们证明，通过适当的信号处理，现成的金属氧化物传感器能够提取快速波动的特征的气体羽流，强烈相关的源距离。我们表明，与一个简单的分析方法，它是可能的解码事件的大，一致的变化，在测量的信号，所谓的“回合”。在风洞实验中，这些发作的频率可以很准确地预测气体源的距离。此外，我们发现，回合计数的方差表明侧风偏移的中心线的气体羽流。我们的研究结果提供了一种替代方法来估计气体源的接近度，这在很大程度上是独立的气体浓度，使用现成的金属氧化物传感器。我们采用的分析方法需要很少的计算资源，适合于低功耗微控制器。(C)2016爱思唯尔B.V.保留所有权利。
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 centre-line 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. (C) 2016 Elsevier B.V. All rights reserved.