Development of TDLAS sensor for diagnostics of CO, H2O and soot concentrations in reactor core of pilot-scale gasifier

Sepman, Alexey; Ögren, Yngve; Gullberg, Marcus; Wiinikka, Henrik

doi:10.1007/s00340-016-6319-x

Cited by 37 publications

(19 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…During the past few decades, many optical-based combustion diagnostic techniques have been developed and become the preferred methods for combustion diagnostics. For example, two-color pyrometers have been employed to measure temperature [1,2], Rayleigh and Raman scattering are used as powerful combustion diagnostic tools for laboratory flames [3,4], laser-induced fluorescence (LIF) was used to determine concentration and/or temperature of certain gaseous species [5,6,7], Laser absorption spectrometry (LAS) was employed to determine gases and soot volume fractions [8,9], etc. Among the numerous combustion diagnostic tools, infrared emission and transmission spectroscopy techniques are especially attractive due to: (1) strong rotational and vibrational transitions of combustion species in the infrared region, (2) separable and specific transitional bands for different species and (3) simplicity of emission and transmission measurements [10,11].…”

Section: Introductionmentioning

confidence: 99%

Machine learning applied to retrieval of temperature and concentration distributions from infrared emission measurements

et al. 2019

View full text Add to dashboard Cite

Inversion of temperature and species concentration distributions from radiometric measurements involves solving nonlinear, ill-posed and high-dimensional problems. Machine Learning approaches allow solving such highly nonlinear problems, offering an alternative way to deal with complex and dynamic systems with good flexibility. In this study, we present a machine learning approach for retrieving temperatures and species concentrations from spectral infrared emission measurements in combustion systems. The training spectra for the machine learning model were synthesized through calculations from HITEMP 2010 for gas mixtures of CO 2 , H 2 O, and CO. The method was tested for different line-of-sight temperature and concentration distributions, different gas path lengths and different spectral intervals. Experimental validation was carried out by measuring spectral emission from a Hencken flat flame burner with a Fourier-transform infrared spectrometer with different spectral resolutions. The temperature fields above the burner for combustion with equivalence ratios of φ =1, φ = 0.8, and φ = 1.4 were retrieved and were in excellent agreement with temperatures deduced from Rayleigh scattering thermometry. performed to address the inverse radiation problems using gradient-based [14] optimization methods. Griffith et al. [15,16] were the first to recognize that measurements of the transmissivity or emissivity of rotational spectral lines of a gas can reveal its temperature. In order to extract temperature, a nonlinear least-square method was used to fit the integrated transmissivity minima. Best et al. [17,18] combined tomography and Fourier transform infrared (FTIR) spectrometer transmission and emission spectra to extract temperature, concentration and soot volume fraction fields. By measuring spectral intensity of the CO 2 4.3 µm band, temperature profiles were retrieved in a number of ways [19,20]. At their time these results were not accurate enough due to lack of an accurate radiation prediction model and robust inverse algorithms. Song et al. [21,22] developed a spectral remote sensing technique to reconstruct CO 2 temperature profiles based on radiative intensity measurements. An accurate narrow band radiation model was employed and several Newton-type regression methods were tested. Due to the nonlinearity and ill-posedness of the problem, regularization of the inverse problems was applied to enforce some degree of smoothness to the solution. It is always difficult to select an appropriate regularization parameter and empirical values for the regularization parameter were employed. Ren and Modest [23] applied the Levenberg-Marquardt optimization method with Tikhonov regularization to reconstruct CO 2 temperature profiles and average concentrations from synthetic line-of-sight spectral intensity data. Two types of temperature profiles were tested for different gas path lengths and different CO 2 spectral bands. A new regularization selection method based on the combination of the L-curve criterion and the discre...

show abstract

Section: Introductionmentioning

confidence: 99%

Machine learning applied to retrieval of temperature and concentration distributions from infrared emission measurements

et al. 2019

View full text Add to dashboard Cite

show abstract

“…State-of-the-art TDLAS for combustion diagnostics are embedded in a variety of applications, such as scramjet combustor, coal gasifier, pulse-detonation combustor, IC engines, and so on [4]- [15]. Li et al designed tunable diode laser sensors for simultaneous measurements of multiple flow parameters of scramjet combustor based on the time division multiplexing scheme.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, Hanson group reported the first diode laser absorption measurements for gas temperature and species concentrations in a pilot-scale coal gasifier [13], [14]. Sepman et al reported the first measurement for accurate real-time in-furnace monitoring of CO, H 2 O and soot volume fraction under pilot-scale gasification conditions using a TDLAS sensor based on single laser near 2.3 μm [15].…”

Section: Introductionmentioning

confidence: 99%

Multiparameter Measurement in Ethylene Diffusion Flame Based on Time-Division Multiplexed Tunable Diode Laser Absorption Spectroscopy

et al. 2019

View full text Add to dashboard Cite

An optical method for measuring soot volume fraction, flame temperature, and concentration of combustion products in a diffusion flame based on time-division multiplexed tunable diode laser absorption spectroscopy technique is presented in this article. By moving the slot burner with an electric platform, two-dimensional profile of soot volume fraction, flame temperature, and gas concentrations along the flame sheet with 1-mm spatial resolution were obtained simultaneously. The flame temperature and soot volume fraction were simultaneously on-line monitored using one distributed feedback diode laser with a center wavelength at 1397.83 nm. Tunable diode laser absorption spectroscopy based temperature measurements in the flame were carried out by two-line thermometry of H 2 O and compared with the thermocouple technique. The attenuation of tunable diode laser intensity caused by soot extinction and gas absorption after transmitting through the diffusion flame was detected. And the soot volume fraction was determined quantitatively with laser extinction based on Rayleigh limit assumption. Two tunable distributed feedback diode lasers with center wavelength at 2001.6 and 2302 nm were used to determine the CO 2 concentration and CO concentration, respectively. The experimental results of soot volume fraction, flame temperature, and the mole fraction of combustion products by varying concentrations of CO 2 added in the diffusion flame were analyzed.

show abstract

“…recently developed a sensor based on a single diode laser at 2.3 µm to measure soot volume fraction, CO and water in an atmospheric gasifier fired with peat powder. [7] Also the influence of fuel composition and burner configuration on the soot volume fraction was investigated. [8] Extinction measurements were performed with two laser diodes at 808 nm and 450 nm.…”

Section: Introductionmentioning

confidence: 99%

Infrared absorption spectrometer for the determination of temperature and species profiles in an entrained flow gasifier

et al. 2017

View full text Add to dashboard Cite

An absorption spectrometer utilizing a tunable distributed feedback diode laser at 2.3 μm and an interband cascade laser at 3.1 μm has been developed to measure temperature and concentrations of CO, CH₄, C₂H₂, and H₂O under gasification conditions. A wavelength division multiplexing approach using a single ZrF₄-fiber was used to measure both wavelength regions simultaneously. The performance of the spectrometer has been tested in laminar flat flames and a heated cell and then applied for measurements at an atmospheric entrained flow gasifier (REGA). A water-cooled optical probe was used to provide optical access at two measurement positions. By moving the burner, axial profiles of temperature and species concentration could be obtained. These profiles were compared with numerical simulations and can be used to validate the simulation.

show abstract

Development of TDLAS sensor for diagnostics of CO, H2O and soot concentrations in reactor core of pilot-scale gasifier

Cited by 37 publications

References 20 publications

Machine learning applied to retrieval of temperature and concentration distributions from infrared emission measurements

Machine learning applied to retrieval of temperature and concentration distributions from infrared emission measurements

Multiparameter Measurement in Ethylene Diffusion Flame Based on Time-Division Multiplexed Tunable Diode Laser Absorption Spectroscopy

Infrared absorption spectrometer for the determination of temperature and species profiles in an entrained flow gasifier

Contact Info

Product

Resources

About