Method of adaptive wide dynamic range gas concentration detection based on optimized direct absorption spectroscopy.
Opt Express
; 31(10): 16770-16780, 2023 May 08.
Article
en En
| MEDLINE
| ID: mdl-37157749
For wide dynamic range gas concentration detection based on tunable diode laser absorption spectroscopy (TDLAS), direct absorption spectroscopy (DAS) and wavelength modulation spectroscopy (WMS) are usually used in combination. However, in some application scenarios such as high-speed flow field detection, natural gas leakage, or industrial production, the requirements of wide-range, fast response and calibration-free must be met. Taking applicability and cost of TDALS-based sensor into consideration, a method of optimized direct absorption spectroscopy (ODAS) based on signal correlation and spectral reconstruction is developed in this paper. This method can achieve adaptive selection of the optimal benchmark spectrum for spectral reconstruction. Moreover, methane (CH4) is taken as an example to carry out the experimental verification. Experimental results proved that the method satisfies wide dynamic range detection of more than 4 orders of magnitude. It is worth noting that when measuring large absorbance with concentration of 75 × 104â
ppm with DAS and ODAS method, respectively, the maximum value of residual is reduced from 3.43 to 0.07. Furthermore, whether measuring gas of small or large absorbance with different concentrations, which vary from 100â
ppm to 75 × 104â
ppm, the correlation coefficient between standard concentrations and inverted concentrations is 0.997, showing the linear consistency of the method in wide dynamic range. In addition, the absolute error is 1.81 × 104â
ppm when measuring large absorbance of 75 × 104â
ppm. It greatly improves the accuracy and reliability with the new method. In summary, the ODAS method can not only fulfill the measurement of gas concentration in wide range, but also further expand the application prospects of TDLAS.
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Banco de datos:
MEDLINE
Tipo de estudio:
Diagnostic_studies
Idioma:
En
Año:
2023
Tipo del documento:
Article