Deep Learning on Synthesized Sensor Characteristics and Transmission Spectra Enabling MEMS-Based Spectroscopic Gas Analysis beyond the Fourier Transform Limit

Abstract

Miniaturized Fourier transform infrared spectrometers serve emerging market needs in many applications such as gas analysis. The miniaturization comes at the cost of lower performance than bench-top instrumentation, especially for the spectral resolution. However, higher spectral resolution is needed for better identification of the composition of materials. This article presents a convolutional neural network (CNN) for 3X resolution enhancement of the measured infrared gas spectra using a Fourier transform infrared (FTIR) spectrometer beyond the transform limit. The proposed network extracts a set of high-dimensional features from the input spectra and constructs high-resolution outputs by nonlinear mapping. The network is trained using synthetic transmission spectra of complex gas mixtures and simulated sensor non-idealities such as baseline drifts and non-uniform signal-to-noise ratio. Ten gases that are relevant to the natural and bio gas industry are considered whose mixtures suffer from overlapped features in the mid-infrared spectral range of 2000–4000 cm−1. The network results are presented for both synthetic and experimentally measured spectra using both bench-top and miniaturized MEMS spectrometers, improving the resolution from 60 cm−1 to 20 cm−1 with a mean square error down to 2.4×10−3 in the transmission spectra. The technique supports selective spectral analysis based on miniaturized MEMS spectrometers.

Measurements and analysis of spectrally resolved spot profile of diffuse reflection micro spectrometers using knife-edge white reference

“…Additionally, the optical head includes optical mirrors and lenses to collect light from the target area on the sample and direct it to the spectral sensor [5] [6]. Illustrative schematic of the whole system is shown in Figure 1 Characterizing the MEMS spectrometer involves evaluating an essential parameters such as the signal to noise ratio [7], the spectral resolution [8] and the spot profile of the light interacting with the sample and finally collected by the spectrometer. This profile serves to quantify the quantity of light that can be effectively coupled from the sample to the spectrometer.…”

Modeling of photonic MEMS Michelson interferometers comprising curved micromirrors under partially coherent light excitation

“…Miniaturized spectrometers are becoming more and more important in various everyday applications [1]. These spectrometers are widely used and their potential is being explored for material analysis in numerous fields including gas sensing [2,3], biochemistry and healthcare applications [4,5], as well as food and feed quality control [6]. Their widespread use is due to their capability to provide satisfactory on-site measurements owing to their small size and good overall performance [7].…”