E-Nose: Multichannel Analog Signal Conditioning Circuit With Pattern Recognition for Explosive Sensing

This paper presents E-Nose, a novel cost-effective, field-deployable portable system that constitutes a 4-channel signal conditioning circuit and multi-coated piezo-resistive micro-cantilever sensors for explosive sensing. E-Nose also features an embedded PCA and K-means based pattern recognition (PR) algorithm for the classification of explosives from non-explosives. The 4-channel configuration is a stack of two 2-channel circuits that are capable of measuring the change in the sensor resistance or capacitance in four optional modes of <inline-formula> <tex-math notation="LaTeX">$\Delta \text{R}$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$\Delta $ </tex-math></inline-formula> R,<inline-formula> <tex-math notation="LaTeX">$\Delta \text{R}$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$\Delta \text{C}$ </tex-math></inline-formula>,<inline-formula> <tex-math notation="LaTeX">$\Delta $ </tex-math></inline-formula> C-<inline-formula> <tex-math notation="LaTeX">$\Delta \text{R}$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$\Delta \text{C}$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$\Delta \text{C}$ </tex-math></inline-formula> by using time multiplexing. The circuit uses a bidirectional AC current excitation method to drive the sensor bridge for significant reduction of DC offset errors, 1/f noise, line noise, and DC drifts. The proposed signal conditioning circuit uses the phase-sensitive synchronous rectification (PSSR) method for AC-to-DC conversion by using balanced demodulation. The circuit can measure a wide range of resistors that range from <inline-formula> <tex-math notation="LaTeX">$100~\Omega $ </tex-math></inline-formula> to 4 <inline-formula> <tex-math notation="LaTeX">$\text{M}\Omega $ </tex-math></inline-formula>, with a sensitivity of 0.4mV/ppm and the worst relative error of 2.6%. The capacitive measurement range is from 100pF to <inline-formula> <tex-math notation="LaTeX">$100~\mu \text{F}$ </tex-math></inline-formula> with the worst relative error of 3.3%. The entire data processing and the PR algorithms run on Raspberry Pi (R-Pi), which is integrated into the E-Nose system. The system performance is tested with MEMS cantilevers for the detection of explosive compounds, such as TNT and its derivatives, RDX and PETN in a controlled environment at a concentration that was as low as 16ppb TNT, 56ppb RDX and 134ppb of PETN. Measurements show that the E-Nose can detect explosives with 77% as true positive results without considering the environmental and mixed vapor effects.

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