Random gas mixtures for efficient gas sensor calibration: Dataset

The dataset was created at the Lab for Measurement Technology (Saarland University). It consists the raw signals (proportional to the logarithmic conductance) of two temperature-modulated semiconductor metaloxide gas sensors (ScioSense AS-MLV and AS-MLV-P2, former AppliedSensor, ams). An exact description of the measurement setup and its results can be found in the open access article: Baur, T., Bastuck, M., Schultealbert, C., Sauerwald, T., and Schütze, A.: Random gas mixtures for efficient gas sensor calibration, J. Sens. Sens. Syst., 9, 411–424, 2020, https://doi.org/10.5194/jsss-9-411-2020 Dataset: The mat-file comprises diffrent datasets: as_mlv: raw signal (~ logarithmic conductance) of the AS-MLV containing 12202 sensor cycles with 12000 data points (@ 100 Hz) as_mlv_p2: raw signal (~ logarithmic conductance) of the AS-MLV-P2 containing 12202 sensor cycles with 12000 data points (@ 100 Hz) as_mlv_targets and as_mlv_p2_targets: acetone: acetone concentration in ppb benzene: benzene concentration in ppb formaldehyde: formaldehyde concentration in ppb, NaN values are undefined formaldehyde concentrations toluene: toluene concentration in ppb carbon_monoxide: carbon monoxide concentration in ppb hydrogen: hydrogen concentration in ppb humidity: relative humidity in %RH voc_sum_ppb: sum of all VOC concentations (acetone, toluene, formaldehyde, benzene) in ppb voc_sum_ugm3: sum of all VOC concentations (acetone, toluene, formaldehyde, benzene) in µg/m3 count: number of the gas mixture exposure, each gas mixture exposure contains approx.10 sensor cycles measurement: number of the measurement, each measurement contains approx.100 gas exposures ranges: marked cycles for the data evaluation with group number