An improved algorithm of temperature compensation for a near infrared multiple-acquisition system based on...

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Optical Engineering

Background:

• Near-infrared (NIR) spectroscopy is a powerful analytical technique with broad applications.
• Temperature fluctuations significantly impact NIR signal acquisition, affecting both qualitative and quantitative analysis.
• Existing methods may lack robustness or introduce complexity in temperature compensation.

Purpose of the Study:

• To develop and validate a novel temperature compensation model for NIR spectroscopy.
• To improve the accuracy and reliability of NIR spectral data.
• To enhance the signal-to-noise ratio (SNR) in NIR measurements.

Main Methods:

• Established a two-dimensional regression model correlating NIR signals with output voltage.
• Experimental validation using six super luminescent diode sources across a temperature range of 293-313 K.
• Applied the compensation scheme to an acousto-optic-tunable-filter (AOTF) system.

Main Results:

• The temperature compensation model effectively reduced the coefficient of variation by a factor of two.
• Demonstrated a significant improvement in signal-noise-ratio after applying the compensation algorithm.
• The method proved effective across various NIR spectral acquisition systems.

Conclusions:

• The proposed temperature compensation model enhances the stability and accuracy of NIR spectroscopy.
• The algorithm offers a low-complexity solution for improving NIR data quality.
• This technique is suitable for diverse NIR spectral acquisition systems, including AOTF-based setups.