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