Data Processing Algorithm for Diagnostics of Combustion Using Diode Laser Absorption Spectrometry.

Area of Science:

• Spectroscopy
• Combustion diagnostics
• Laser applications

Background:

• Accurate temperature measurement is crucial for understanding combustion processes.
• Traditional methods using absorption spectroscopy often struggle with baseline (BL) fitting, introducing errors.
• Diode-laser absorption spectroscopy offers high sensitivity for in-situ measurements.

Purpose of the Study:

• To develop a new algorithm for evaluating integral line intensity to infer accurate temperatures in hot zones.
• To overcome limitations associated with baseline fitting in spectral analysis.
• To improve the precision of temperature diagnostics in combustion environments.

Main Methods:

• Proposed an algorithm based on orthogonal polynomial expansion of experimental and simulated spectra.
• Subtracted the first three components of the polynomial expansion from spectra before fitting.
• Tested the algorithm using simulated absorption spectra with added noise and parabolic baseline.

Main Results:

• The algorithm successfully obtained correct integral line intensities and temperature values.
• Evaluations showed a standard deviation better than 60 K at 1000 K for line half-widths up to 0.6 cm⁻¹.
• The method demonstrated robustness against white noise and parabolic baselines.

Conclusions:

• The developed algorithm provides accurate temperature estimations in hot zones without the need for baseline fitting.
• This approach enhances the reliability of combustion diagnostics using diode-laser absorption spectroscopy.
• The method is effective for spectral line intensity evaluation and temperature inference.