Hybrid Pattern Recognition for Rapid Explosive Sensing with Comprehensive Analysis

Palaparthy, VS and Doddapujar, SN and Surya, SG and Chandorkar, SA and Mukherji, S and Baghini, MS and Ramgopal Rao, V (2021) Hybrid Pattern Recognition for Rapid Explosive Sensing with Comprehensive Analysis. In: IEEE Sensors Journal, 21 (6). pp. 8011-8019.

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Abstract

This paper presents a hybrid pattern recognition with temperature compensation (HPR-TC) used within an E-Nose system. HPR-TC with E-nose has the novelty, amongst MEMS sensor platforms, of having two modes of operation i.e., rapid mode of detection to be used in time-critical conditions and comprehensive analysis mode for improved detection accuracy. Two modes of operations in HPR-TC are possible because of the implementation of hybrid PR featuring a combination of two different data analysis techniques for explosive sensing. The first part of the hybrid PR is the binary PR based on threshold-based detection and the second one is the analog PR based on PCA and K-mean. The E-Nose system with proposed HPR-TC is validated with two different highly sensitive MEMS sensor types, i.e., SU8 and Si3Nx piezo-resistive cantilever. These MEMS sensors are coated with surface receptors, 4-MBA, 6-MNA and 4-ATP, to improve the selectivity. The E-Nose system can detect explosive compounds such as TNT, RDX, and PETN, in a controlled environment at a concentration as low as 16ppb of TNT, 56ppb of RDX and 134ppb of PETN. Furthermore, measurements show that E-Nose with temperature compensated binary PR can detect the explosives with a detection accuracy higher than 74% as true positives and higher than 79% as true negatives in a short time, within initial 17 seconds of the experiment. However, the temperature compensated analog PR gives a detailed classification of explosives with a higher detection accuracy of 80% as true positives and 86% as true negatives after approximately 95 seconds.

Item Type:	Journal Article
Publication:	IEEE Sensors Journal
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords:	Electronic nose; Explosives; Pattern recognition systems; Silicon compounds, Comprehensive analysis; Controlled environment; Data analysis techniques; Detailed classification; Explosive compounds; Piezo-resistive cantilevers; Temperature compensated; Temperature compensation, Explosives detection
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	13 Apr 2023 09:49
Last Modified:	13 Apr 2023 09:49
URI:	https://eprints.iisc.ac.in/id/eprint/80617

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