TDLAS detection of propylene with complex spectral features

To satisfy the need for propylene measurement in the olefin production process, Tunable Diode Laser Absorption Spectroscopy (TDLAS) was studied to improve analytical performance. In this paper, a numerical simulation approach is proposed using absorbance from a spectral database to obtain the optimized design parameters, which is independent of spectral features. In the simulation, the effect of a wider linewidth laser on the absorbance profile was considered. Through the comparison of simulation results and experimental collection, the TDLAS-based propylene analysis apparatus was developed correspondingly. It has a 1 628.5 nm center wavelength broad-tuning DFB laser. A differential method was utilized in demodulated spectral acquisition to eliminate bias voltage. The multivariate linear regression model was employed to reduce the strong spectral interference from the background components in the analysis. Based on the simulated field test, the max relative error is 0.55% in the 0~1% range for the step test. For the long-term test, the standard deviation (1σ) is 9.3×10⁻⁶ for 0.2% propylene concentration. The best standard deviation is 1.33×10⁻⁶ at 221.9 s of integration time through Allen variance analysis. In the anti-interference test, the max error of 19.17×10⁻⁶ is demonstrated for 0.2% propylene concentration while methane and ethylene concentrations vary. The disadvantages of traditional methods such as the Gas Chromatogram (GC) and soft measurement methods are overcome by modulated absorption spectroscopy. The TDLAS system for heavy hydrocarbon detection with complex spectral features was demonstrated to have distinct advantages in precision, stability and interference suppression through multivariate regression modeling.