[1] Wood M P, Ozanyan K B. Simultaneous temperature, concentration, and pressure imaging of water vapor in a turbine engine[J]. IEEE Sensors Journal, 15, 545-551(2015).

[2] Chen J H, Sun C Y, Lin Z Q et al. Research on CO2 concentration detection method based on TDLAS technology[J]. Journal of Electronic Measurement and Instrumentation, 36, 229-235(2022).

[3] Jeon M G, Hong J W, Doh D H et al. A study on two-dimensional temperature and concentration distribution of propane-air premixed flame using CT-TDLAS[J]. Modern Physics Letters B, 7, 2040020(2020).

[4] Li J Y, Zhao H, Yang X T et al. Research and application progress on laser absorption spectroscopy technology for 2D and 3D imaging measurement[J]. Laser & Optoelectronics Progress, 59, 1900005(2022).

[5] Liu C Y, Xu Z Y, Huang A et al. TDLAT measurement method for outlet temperature profile of combustor based on wavelength modulation spectroscopy technology[J]. Journal of Aerospace Power, 38, 116-126(2023).

[6] Qiu C C, Cao L, Chen X L et al. TDLAS online measurement system for plume temperature of ramjet engine[J]. Chinese Journal of Scientific Instrument, 42, 70-77(2021).

[7] Li J Y, Li L H, Zhao S et al. Application research of tunable diode laser absorption spectroscopy in petroleum industry[J]. Laser & Optoelectronics Progress, 59, 1300006(2022).

[8] Xu J, Li Y F, Cheng Y et al. Development of methane leakage telemetry system based on TDLAS-WMS[J]. Laser & Optoelectronics Progress, 60, 0628006(2023).

[9] Liu C, Xu L J. Laser absorption spectroscopy for combustion diagnosis in reactive flows: a review[J]. Applied Spectroscopy Reviews, 54, 1-44(2019).

[10] Yao J Y, Zheng X Z, Li H J et al. Research on optical tomography based on optimized landweber algorithm[J]. Laser & Optoelectronics Progress, 60, 1611003(2023).

[11] Si J J, Liu X, Wang X L et al. Laser absorption spectroscopy tomography based on the expected patch Log likelihood[J]. Chinese Journal of Scientific Instrument, 44, 248-256(2023).

[12] Huang J Q, Liu H C, Dai J H et al. Reconstruction for limited-data nonlinear tomographic absorption spectroscopy via deep learning[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 218, 187-193(2018).

[13] Si J J, Fu G C, Cheng Y B et al. Tunable diode laser absorption tomography based on hierarchical discretization and residual network[J]. Journal of Electronics & Information Technology, 44, 2539-2546(2022).

[14] Si J J, Wang X L, Cheng Y B et al. Temperature tomography for combustion field based on hierarchical vision transformer and multi-scale features merging[J]. Journal of Electronics & Information Technology, 45, 3511-3519(2023).

[15] Cao Z, Gao X, Lu F H et al. Laser absorption spectral tomography for dynamical combustion monitoring[J]. Chinese Journal of Lasers, 49, 1904002(2022).

[16] He K M, Zhang X Y, Ren S Q et al. Delving deep into rectifiers: surpassing human-level performance on ImageNet classification[C], 1026-1034(2015).

[17] Xu J, Li Z S, Du B W et al. Reluplex made more practical: Leaky ReLU[C], 1-7(2020).

[18] Mcgrattan K B, Baum H R, Rehm R G et al[M]. Fire dynamics simulator-technical reference guide(2000).

[19] Patankar S V[M]. Numerical heat transfer and fluid flow(2018).

[20] Dong C, Loy C C, He K M et al. Image super-resolution using deep convolutional networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, 295-307(2016).

[21] Lu Z S, Li J C, Liu H et al. Transformer for single image super-resolution[C], 456-465(2022).

[22] Si J J, Lü D C, Zhang R et al. Laser absorption spectroscopy tomography based on cartoon-texture model[J]. Chinese Journal of Lasers, 51, 0611001(2024).

[23] Enemali G, Zhang R, McCann H et al. Cost-effective quasi-parallel sensing instrumentation for industrial chemical species tomography[J]. IEEE Transactions on Industrial Electronics, 69, 2107-2116(2022).

[24] Bao Y, Zhang R, Enemali G et al. Relative entropy regularized TDLAS tomography for robust temperature imaging[J]. IEEE Transactions on Instrumentation and Measurement, 70, 4501909(2021).

[25] Si J J, Fu G C, Liu X et al. A spatially progressive neural network for locally/globally prioritized TDLAS tomography[J]. IEEE Transactions on Industrial Informatics, 19, 10544-10554(2023).