What question did this study set out to answer?

The aim is to improve FTIR spectroscopy accuracy for high-concentration CO2 monitoring by overcoming saturation effects.

June 1, 2026

FTIR Quantitative Analysis of High-Concentration CO 2 : Overcoming Saturation Effects via an MIV-GWO-ELM Integration Framework

Key Points

The aim is to improve FTIR spectroscopy accuracy for high-concentration CO2 monitoring by overcoming saturation effects.
Developed a hybrid MIV-GWO-ELM framework for spectral feature selection and parameter optimization.
Conducted experiments with CO2 concentrations ranging from 5.0% to 9.75%.
Compared model performance against baseline ELM and Levenberg–Marquardt algorithm.
Achieved a MAE reduction of 79.72%, RMSE reduction of 79.50%, and MAPE reduction of 78.58% compared to baseline ELM.
Outperformed the Levenberg–Marquardt algorithm and multilayer perceptron with error reductions of 71% and 58%, respectively.
Maintained a training time of under 13 seconds.

Abstract

The quantitative analysis of Fourier transform infrared (FTIR) spectroscopy for monitoring high-concentration industrial gases, such as CO2 in steel manufacturing, is severely challenged by spectral absorption saturation, which introduce strong nonlinearities and degrade the accuracy of traditional methods. To address this, we propose a hybrid inversion framework, the mean impact value-enhanced gray wolf optimizer-based extreme learning machine (MIV-GWO-ELM), which synergizes intelligent spectral feature selection via MIV to mitigate saturation effects and employs GWO for the global optimization of ELM’s initial parameters to enhance stability. Experimental results on high-concentration CO2 (5.0%–9.75%) demonstrate the model’s performance, reducing MAE, RMSE, and MAPE by 79.72%, 79.50%, and 78.58%, respectively, compared to the baseline ELM, while also outperforming the Levenberg–Marquardt algorithm and a multilayer perceptron with approximate error reductions of 71% and 58%, all within a training time of under 13 s. This work effectively enhances the precision of FTIR systems under nonlinear conditions, offering a reliable and efficient solution for industrial gas monitoring and a promising strategy for complex spectroscopic inversions.

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