This paper addresses problems arising from in situ measurement of gas content and temperature. Such measurements can be considered indirect. Transmittance or natural radiation of a gas is measured directly. The latter method (spectral radiation measurement) is often called spectral remote sensing. Its primary uses are in astronomy and in the measurement of atmospheric composition. In industrial processes, in situ spectroscopic measurements in the plant are often made with an open path Fourier Transform Infrared (FTIR) spectrometer. The main difficulty in this approach is related to the calibration process, which often cannot be carried out in the manner used in the laboratory. Spectral information can be obtained from open path spectroscopic measurements using mathematical modeling, and by solving the inverse problem. Determination of gas content based on spectral measurements requires comparison of the measured and modeled spectra. This paper proposes a method for the simultaneous use of multiple lines to determine the gas content. The integrated absorptions of many spectral lines permits calculation of the average band absorption. An inverse model based on neural networks is used to determine gas content based on mid-infrared spectra at variable temperatures.
Open-Path Fourier Transform Infrared OP-FTIR spectrometers are commonly used for the measurement of atmospheric pollutants and of gases in industrial processes. Spectral interpretation for the determination of gas concentrations is based on the HITRAN database line-by-line modeling method. This article describes algorithms used to model gas spectra and to determine gas concentration under variable temperatures. Integration of individual rotational lines has been used to reduce the impact of spectrometer functions on the comparison of both measured and synthetic modeled spectra. Carbon monoxide was used as an example. A new algorithm for gas concentration retrieval consisting of two ensemble methods is proposed. The first method uses an ensemble of local models based on linear and non-linear PLS (partial least square) regression algorithms, while the second is an ensemble of a calibration set built for different temperatures. It is possible to combine these methods to decrease the number of regression models in the first ensemble. These individual models are appropriate for specific measurement conditions specified by the ensemble of the calibration set. Model selection is based on comparison of gas spectra with values determined from each local model
The paper presents a method of measuring the angle of rotation and twist using a tilted fibre Bragg grating
(TFBG) periodic structure with a tilt angle of 6◦, written into a single-mode optical fibre. It has been shown
that the rotation of the sensor by 180◦ causes a change in the transmission coefficient from 0.5 to 0.84 at
a wavelength of 1541.2 nm. As a result of measurements it was determined that the highest sensitivity can
be obtained for angles from 30◦ to 70◦ in relation to the basic orientation. The change in the transmission
spectrum occurs for cladding modes that change their intensity with the change in the polarization of light
propagating through the grating. The same structure can also be used to measure the twist angle. The
possibility of obtaining a TFBG twist by 200◦ over a length of 10 mm has been proved. This makes it
possible to monitor both the angle of rotation and the twist of an optical fibre with the fabricated TFBG.