暴露于湍流气体混合物数据集的气体传感器阵列，8个化学电阻气体传感器

Data Set Information: A chemical detection platform composed of 8 chemo-resistive gas sensors was exposed to turbulent gas mixtures generated naturally in a wind tunnel. The acquired time series of the sensors are provided. The experimental setup was designed to test gas sensors in realistic environments. Traditionally, chemical detection systems based on chemo-resistive sensors include a gas chamber to control the sample air flow and minimize turbulence. Instead, we utilized a wind tunnel with two independent gas sources that generate two gas plumes. The plumes get naturally mixed along a turbulent flow and reproduce the gas concentration fluctuations observed in natural environments. Hence, the gas sensors can capture the spatio-temporal information contained in the gas plumes. a) Chemical detection platform: The chemical detection platform was composed of 8 MOX gas sensors that generate a time-dependent multivariate response to the different gas stimuli. The utilized sensors were made commercially available by Figaro (TGS2611, TGS2612, TGS2610, TGS2600, TGS2602 TGS2620). The operating temperature of the sensors was controlled by the built-in heater, which was kept at a constant voltage of 5V. The detection platform also includes Temperature and Relative Humidity sensors. The generated sensors' responses were acquired at a sampling rate of 20 ms for the whole duration of the experiment. b) Wind tunnel: In order to generate two independent gas plumes in an open environment, we built a 2.5 m x 1.2 m x 0.4 m wind tunnel facility with two gas sources (labeled as source1 and source2). Each source was controlled independently to release the selected volatiles at different flow rates, which generated different concentration levels in the sensors' position. The wind generator created a turbulent flow that constantly displaced the introduced volatiles towards the exhaust outlet. c) Experimental protocol: We exposed the detection unit to mixtures of Ethylene with Methane or Carbon Monoxide. The mixtures were originated releasing Ethylene at source1 and releasing Methane / Carbon Monoxide at source2. Each volatile was released at four different flows (zero z, low l, medium m, and high h), providing up to 30 different mixture configurations: 15 mixtures of Ethylene with CO (h+h, h+m, h+l, a€|, z+h, z+m, z+l) and 15 mixtures of Ethylene with Methane. Each configuration was repeated 6 times. Hence, the complete dataset was composed of 180 measurements, which were performed in a random order. By means of a GCMS system, the mean concentration levels at the sensors' location were estimated: Ethylene (l: 31 ppm, m: 46 ppm, h: 96 ppm), CO (l: 270 ppm, m: 397 ppm, h: 460 ppm), Methane (l: 51 ppm, m: 115 ppm, h: 131 ppm). It is worth noting that GC-MS systems only provide the mean value of the concentration and are not sensitive to concentration fluctuations. Each measurement, which had a total duration of 300 seconds, was performed as follows: Initially no gas was released and clean air flowed along the wind tunnel. 60 seconds after, both sources started to release the corresponding volatile at the specified flow rate. The duration of the gas release was 180 s. Finally, the system acquired the recovery to the baseline for another 60 s. Attribute Information: The dataset is presented in 180 text files, where each file corresponds to a different measurement. The filenames identify the measurements as follows: The first 3 characters of the filename are a local identifier, which is not related to the order of the measurements; characters 5-8 indicate the concentration level of Ethylene released at source2 (n: zero, L: Low, M: Medium, H: High); the last 4 characters indicate the gas released at source1 (Me: Methane, CO: Carbon Monoxide) and the concentration level. For example, file 007_Et_L_Me_H contains time series acquired when Ethylene was released at Low concentration (31 ppm, mean concentration) and Methane at High concentration (131 ppm, mean concentration). Each file includes the acquired time series, presented in 11 columns: Time (s), Temperature (oC), Relative Humidity (%), and the readings of the 8 gas sensors: TGS2600, TGS2602, TGS2602, TGS2620, TGS2612, TGS2620, TGS2611, TGS2610. The readings can be converted to sensor resistance by Rs(KOhm)=10*(3110-A)/A, where A is the acquired value. The raw acquired time series are provided, and also time series down sampled at 100 ms. Relevant Papers: The description of the experimental setup and chemical detection platform can be found in [1]. The wind tunnel was adapted from a previous setup to include two independent gas sources. See [2] for additional details on the experimental setup. [1]: Jordi Fonollosa, Irene Rodr?-guez-Lujan, Marco Trincavelli, Alexander Vergara and Ramon Huerta Chemical discrimination in turbulent gas mixtures with MOX sensors validated by gas chromatography-mass spectrometry. Sensors 2014. [2]: Vergara, Alexander, Jordi Fonollosa, Jonas Mahiques, Marco Trincavelli, Nikolai Rulkov, and Ramon Huerta. 'On the performance of gas sensor arrays in open sampling systems using Inhibitory Support Vector Machines.' Sensors and Actuators B: Chemical 185 (2013): 462-477. Citation Request: The following citation is requested if you use the dataset: Jordi Fonollosa, Irene Rodriguez-Lujan, Marco Trincavelli, Alexander Vergara and Ramon Huerta Chemical discrimination in turbulent gas mixtures with MOX sensors validated by gas chromatography-mass spectrometry. Sensors 2014. Creators: Jordi Fonollosa (fonollosa '@'ucsd.edu) BioCircutis Institute University of California San Diego San Diego, California, USA Donors of the Dataset: Jordi Fonollosa (fonollosa '@'ucsd.edu) Irene Rodriguez-Lujan (irrodriguezlujan '@' ucsd.edu) Marco Trincavelli (marco.trincavelli '@' oru.se) Alexander Vergara Ramon Huerta (rhuerta '@' ucsd.edu)

数据集信息：本数据集包含一套由8个电阻式气体传感器组成的化学检测平台在风洞中自然产生的湍流混合气体环境下采集的传感器时间序列数据。本实验装置旨在模拟真实环境以开展气体传感器测试。
传统基于电阻式传感器的化学检测系统通常配备气室以控制采样气流并最大限度抑制湍流。本研究则采用带有两路独立气源的风洞，可生成两股气体羽流。两股羽流随湍流自然混合，复现了自然环境中观测到的气体浓度波动特征，使气体传感器能够捕捉气体羽流蕴含的时空信息。
a) 化学检测平台：本化学检测平台由8个金属氧化物(MOX)气体传感器组成，可对不同气体刺激产生随时间变化的多变量响应。所用传感器均为Figaro公司的商用产品，型号包括TGS2611、TGS2612、TGS2610、TGS2600、TGS2602及TGS2620。传感器的工作温度由内置加热器控制，维持在5V恒定电压下。检测平台还集成了温度与相对湿度传感器。整个实验过程中，传感器响应数据均以20 ms的采样率进行采集。
b) 风洞装置：为在开放环境中生成两路独立的气体羽流，本研究搭建了尺寸为2.5 m × 1.2 m × 0.4 m的风洞设施，配备两路独立气源（标记为source1与source2）。每一路气源均可独立控制，以不同流速释放选定的挥发性有机物，从而在传感器部署位置产生不同的气体浓度。风洞的送风系统可生成湍流，将引入的挥发性有机物持续输送至排气口。
c) 实验方案：本研究将检测单元暴露于乙烯与甲烷，或乙烯与一氧化碳的混合气体环境中。混合气体的生成方式为：在source1释放乙烯，在source2释放甲烷/一氧化碳。每种挥发性有机物均以四种不同流速释放（零流量z、低流量l、中流量m与高流量h），总计可生成30种不同的混合气体配置：15种乙烯与一氧化碳混合体系（h+h、h+m、h+l、……、z+h、z+m、z+l）以及15种乙烯与甲烷混合体系。每种配置重复6次实验，因此完整数据集共包含180组测量数据，实验顺序均为随机排布。通过气相色谱-质谱联用仪(GC-MS)可估算传感器部署位置的平均气体浓度：乙烯（l: 31 ppm，m: 46 ppm，h: 96 ppm）、一氧化碳（l: 270 ppm，m: 397 ppm，h: 460 ppm）、甲烷（l: 51 ppm，m: 115 ppm，h: 131 ppm）。需注意，GC-MS仅能提供浓度平均值，无法感知浓度波动。每组测量总时长为300秒，流程如下：初始阶段无气体释放，风洞内仅流通洁净空气；60秒后，两路气源开始以指定流速释放对应挥发性有机物，气体释放时长为180秒；最后系统继续采集60秒以记录传感器恢复至基线的过程。
属性信息：本数据集以180个文本文件形式存储，每个文件对应一组不同的测量数据。文件名的命名规则如下：文件名前3个字符为本地标识符，与测量顺序无关；第5至8个字符表示source2释放的乙烯浓度等级（n: 零流量，L: 低流量，M: 中流量，H: 高流量）；最后4个字符表示source1释放的气体类型（Me: 甲烷，CO: 一氧化碳）及其浓度等级。例如，文件007_Et_L_Me_H对应的测量场景为：乙烯以低流量（平均浓度31 ppm）释放，甲烷以高流量（平均浓度131 ppm）释放，此时采集的时间序列数据。每个文件包含采集到的时间序列数据，共11列：时间（单位：秒）、温度（单位：摄氏度）、相对湿度（单位：%）以及8个气体传感器的读数：TGS2600、TGS2602、TGS2602、TGS2620、TGS2612、TGS2620、TGS2611、TGS2610。传感器读数可通过公式Rs(单位：千欧)=10*(3110-A)/A转换为传感器内阻，其中A为采集到的原始读数。本数据集同时提供原始采集的时间序列数据，以及以100 ms为间隔降采样后的时间序列数据。
相关研究文献：实验装置与化学检测平台的详细说明可参见文献[1]。本研究的风洞装置改编自已有方案，并新增了两路独立气源。关于实验装置的更多细节可参见文献[2]。[1]: Jordi Fonollosa, Irene Rodríguez-Lujan, Marco Trincavelli, Alexander Vergara 与 Ramon Huerta. 基于金属氧化物传感器的湍流混合气体化学识别：气相色谱-质谱联用仪验证. Sensors, 2014. [2]: Vergara, Alexander, Jordi Fonollosa, Jonas Mahiques, Marco Trincavelli, Nikolai Rulkov, 与 Ramon Huerta. 基于抑制支持向量机的开放采样系统中气体传感器阵列性能研究. Sensors and Actuators B: Chemical, 185(2013): 462-477.
引用要求：若使用本数据集，请遵循以下引用格式：Jordi Fonollosa, Irene Rodríguez-Lujan, Marco Trincavelli, Alexander Vergara 与 Ramon Huerta. 基于金属氧化物传感器的湍流混合气体化学识别：气相色谱-质谱联用仪验证. Sensors, 2014.
数据集创建者：Jordi Fonollosa（邮箱：fonollosa '@' ucsd.edu），美国加利福尼亚州圣地亚哥市加州大学圣地亚哥分校生物电路研究所（BioCircutis Institute）。数据集捐赠者：Jordi Fonollosa（fonollosa '@' ucsd.edu）、Irene Rodríguez-Lujan（irrodriguezlujan '@' ucsd.edu）、Marco Trincavelli（marco.trincavelli '@' oru.se）、Alexander Vergara、Ramon Huerta（rhuerta '@' ucsd.edu）。

搜集汇总

背景与挑战

背景概述

该数据集包含8个化学电阻气体传感器在湍流气体混合物中的响应数据，适用于研究传感器在真实环境下的性能表现。数据集由180个测量文件组成，涵盖了乙烯与甲烷或一氧化碳的不同浓度组合，为气体传感器研究提供了丰富的实验数据。