Multi-unit calibration rejects inherent device variability of chemical sensor arrays

Abstract

Inherent sensor variability limits mass-production applications for metal oxide (MOX) gas sensor arrays because calibration for replicas of a sensor array needs to be performed individually. Recently, calibration transfer strategies have been proposed to alleviate calibration costs of new replicas, but they still require the acquisition of transfer samples. In this work, we present calibration models that can be extended to uncalibrated replicas of sensor arrays without acquiring new samples, i.e., general or global calibration models. The developed methodology consists in including multiple replicas of a sensor array in the calibration process such that sensor variability is rejected by the general model. Our approach was tested using replicas of a MOX sensor array in the classification task of six gases and synthetic air, presented at different background humidity and concentration levels. Results showed that direct transfer of individual calibration models provides poor classification accuracy. However, we also found that general calibration models kept predictive performance when were applied directly to new copies of the sensor array. Moreover, we explored, through feature selection, whether particular combinations of sensors and operating temperatures can provide predictive performances equivalent to the calibration model with the complete array, favoring thereby the existence of more robust calibration models.

Real-Time Sensor Response Characteristics of 3 Commercial Metal Oxide Sensors for Detection of BTEX and Chlorinated Aliphatic Hydrocarbon Organic Vapors

“…Manufacturers generally provide little information or recommendations for addressing the known drift and variable responses of resistive sensors to different chemicals, typically stating only that MOx sensors require regular recalibration. Close examination of real-time sensor responses is required in order to develop data analysis algorithms that address the geospatial and time-dependent variability inherent in large field sampling, as well as sensitivity, accuracy and response dynamics associate with collection of such real-time monitoring data [19]. Sensor arrays have been widely proposed to overcome some of this variability, however, calibration of such arrays is particularly complex with respect to model development, fitting, and choice of calibration gas mixtures [20,21].…”

Evaluating and improving the reliability of gas-phase sensor system calibrations across new locations for ambient measurements and personal exposure monitoring

“…Other research has utilized windowed piecewise direct standardization to transform the sensor readings from a slave sensor to a calibrated master for single gas concentrations (Yan and Zhang, 2015) and direct standardization for a range of gases and concentrations over a longer timeframe (Fonollosa et al, 2016). While previous efforts utilized single master sensors, Solórzano et al (2018) showed that including multiple master sensors in a calibration model can improve the robustness of the overall model. Similar findings were reached by Smith et al (2017) when investigating sensor drift whereby an ensemble model was generated by training models for multiple sensors and the prediction was reported as the cluster median.…”

Calibration Update and Drift Correction for Electronic Noses and Tongues

“…Global calibration can be applied to the calibration transfer between electronic nose instruments, in which case source of undesirable variation is differences in response characteristics between sensors of the same composition (Solórzano et al, 2018 ). General calibration model is calculated using measurements made with several replicas of sensor array and is expected to include variations between different sensor arrays of the same composition.…”