Abstract
Water vapor temperatures in a heating device were measured by ultra-low sampled and high-precision tunable diode laser spectroscopy (TDLAS) Bichromatic distributed feedback (DFB) lasers were used as light sources. Sampled data at an ultra-low rate was collected after laser passing through a low-pass filter and served as the inputs of an artificial neural network. Classical direct absorption spectroscopy using the line-shape fitting method provided the training dataset, i.e., the integrated absorbances. The proposed method required an ultra-low sampling rate, i.e., only 1/50 of the classical method, but its calculation speed was nearly 14,000 times faster. Also, the proposed method yielded satisfying estimates at temperatures uncovered by the training dataset and was insensitive to random noises.
Highlights
In recent years, tunable diode laser spectroscopy (TDLAS) attracts attention all over the world for gas detections in industrial production and environmental protections [1]–[3]
Among available contactless laser spectroscopic techniques, such as laser-induced fluorescence (LIF) [5] and coherent anti-Stokes Raman scattering (CARS) [6], TDLAS is more suitable for onsite applications for its economic cost, simple structure, and robust performances in harsh environments [7], [8]
For the wavelength modulation spectroscopy (WMS) method, a high-frequency sinusoidal signal is usually imposed on the low-frequency saw-tooth/sinusoidal signal, and these signals modulate the laser in both intensity and wavenumber [11]
Summary
Tunable diode laser spectroscopy (TDLAS) attracts attention all over the world for gas detections in industrial production and environmental protections [1]–[3]. For the WMS method, a high-frequency sinusoidal signal is usually imposed on the low-frequency saw-tooth/sinusoidal signal, and these signals modulate the laser in both intensity and wavenumber [11]. The absorption spectrum is emigrated to the vicinity of the modulation frequency to suppress background noises [16], and it enables successful applications of the WMS method [17], [18]. These modulating signals in WMS require a high sampling rate for the light intensity acquisition. For a TDLAS gas thermometry, only integrated absorbances over different spectrum, i.e., two individual spectral lines, are extracted from the intensity data. A low sampling rate is feasible to extract these absorbances
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