TDLAS gas concentration calibration curve fitting based on improved LS algorithm

Zhilong Zhang; Yifeng Zhu; Ansheng Zhao; Liping Liang; He Zhang

doi:10.1117/12.2668265

20 April 2023 TDLAS gas concentration calibration curve fitting based on improved LS algorithm

Zhilong Zhang, Yifeng Zhu, Ansheng Zhao, Liping Liang, He Zhang

Proceedings Volume 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022); 126023E (2023) https://doi.org/10.1117/12.2668265
Event: International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 2022, Changchun, China

Abstract

Tunable diode laser absorption spectroscopy (TDLAS) technology is one of the spectral detection technologies, and its advantages include high selectivity, high sensitivity, and fast response speed. The detection accuracy of the TDLAS gas detection system is closely related to the calibration curve. When calibrating, the least-squares algorithm is often used for fitting. However, the fitting algorithm is inaccurate in the inversion of the coefficient matrix, which causes the system to detect excessive gas concentration errors. Therefore, an improved LS algorithm is proposed to solve the above problems. The experiment is verified by detecting the concentration of carbon dioxide gas. The central wavelength of the gas is selected at 1573.2 nm, and the range to be measured is 10%~30%. The error sum of the improved fitting algorithm is 3.1955×10^-5, the mean square error is 5.3259×10^-6, the standard deviation is 2.3×10^-3, and the correlation coefficient is 0.9998. In the whole concentration range, the absolute value of the relative error of the gas concentration obtained by its inversion is less than 3.0479%. The reliability of the improved fitting algorithm is verified, the fitting effect is improved, and the accuracy of TDLAS gas detection is improved.

Citation Download Citation

Zhilong Zhang, Yifeng Zhu, Ansheng Zhao, Liping Liang, and He Zhang "TDLAS gas concentration calibration curve fitting based on improved LS algorithm", Proc. SPIE 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 126023E (20 April 2023); https://doi.org/10.1117/12.2668265

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Matrices

Signal detection

Technology

Calibration

Detection and tracking algorithms

Semiconductor lasers

Laser frequency

Show All Keywords

Keywords/Phrases

Search In:

Publication Years