Fast and robust gas identification system using an integrated gas sensor technology and Gaussian mixture models

Abstract

Abstract-Among the most serious limitations facing the success of future consumer gas identification systems are the drift problem and the real-time detection due to the slow response of most of today's gas sensors. This paper shows that the combination of an integrated sensor array and a Gaussian mixture model permits success in gas identification problems. An integrated sensor array has been designed with the aim of combustion gases identification. Our identification system is able to quickly recognize gases with more than 96% accuracy. Robust detection is introduced through a drift counteraction approach based on extending the training data set using a simulated drift.

A Robust and Low‐Complexity Gas Recognition Technique for On‐Chip Tin‐Oxide Gas Sensor Array

“…The small number of needed parameters and low complexity of the required computations suggest efficient on-chip hardware implementation of the In continuous line, the results of the proposed recognition system without retraining. In dashed line, the results obtained in [15] with retraining. In dashed-dot line, the results obtained in [15] without retraining.…”

“…In dashed-dot line, the results obtained in [15] without retraining. The proposed method outperforms the performances in [15] and shows a quite invariance of the recognition accuracy of the drifted measurements, even the system is trained on a nondrifted measurements. recognition system.…”

“…The identification results of the drifted measurements using the system trained on a nondrifted measurements are shown in Figure 4 and compared to the recognition performances obtained in [15]. The proposed technique shows a higher accuracy than the one achieved in [15] with and without retraining the system. It is also important to note the significant invariance of our performance when increasing the drift.…”

A Committee Machine Gas Identification System Based on Dynamically Reconfigurable FPGA

“…Three different sensing films are used to implement the sensor array. One sensor is based on Au/SnO (sensor 1), another sensor is based on Pt/Cu(0.16 wt%)-SnO (sensor 2), and the remaining two sensors are based on Pt/SnO (sensors 3 and 4) [13]. Totally, two chips were used and calibrated by tuning their selectivity to a given set of gases using the temperature parameter.…”

“…After the gas pattern is obtained from the sensor array, Euclidean normalization is performed to reduce the pattern dispersion induced by concentration changes. Normalization has been previously employed in gas discrimination applications where the identification must be based on signature pattern, and not on the concentration dependent amplitudes [13]. Normalization is also useful to set the range of values for sensors output.…”