Multispectral radiometric temperature measurement algorithm for turbine blades based on moving narrow-band spectral windows

Zhao, Yuan; Lv, Jinguang; Zheng, Kaifeng; Jin, Tao; Qin, Yuxin; Wang, Weibiao; Wang, Chao; Liang, Jinsong

doi:10.1364/oe.414844

Cited by 20 publications

(4 citation statements)

References 33 publications

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“…Usually, multiple measurement points need to be deployed to reflect the temperature distribution within the combustion field, which cannot meet the demand for high-quality field distribution measurements, and the contact measurements will destroy the combustion flow field, affecting the measurement results [1,2]. In contrast, infrared thermography and radiation thermometry, as two types of non-contact measurement methods, do not interfere with the measurement area and more easily achieve the field distribution measurement [3,4], but these methods usually measure the temperature of the surface of the combustion field, and it is difficult to meet the needs of temperature measurement inside the combustion field.…”

Section: Introductionmentioning

confidence: 99%

Multi-View Synthesis of Sparse Projection of Absorption Spectra Based on Joint GRU and U-Net

Shi,

Hao,

Huang

et al. 2024

Applied Sciences

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Tunable diode laser absorption spectroscopy (TDLAS) technology, combined with chromatographic imaging algorithms, is commonly used for two-dimensional temperature and concentration measurements in combustion fields. However, obtaining critical temperature information from limited detection data is a challenging task in practical engineering applications due to the difficulty of deploying sufficient detection equipment and the lack of sufficient data to invert temperature and other distributions in the combustion field. Therefore, we propose a sparse projection multi-view synthesis model based on U-Net that incorporates the sequence learning properties of gated recurrent unit (GRU) and the generalization ability of residual networks, called GMResUNet. The datasets used for training all contain projection data with different degrees of sparsity. This study shows that the synthesized full projection data had an average relative error of 0.35%, a PSNR of 40.726, and a SSIM of 0.997 at a projection angle of 4. At projection angles of 2, 8, and 16, the average relative errors of the synthesized full projection data were 0.96%, 0.19%, and 0.18%, respectively. The temperature field reconstruction was performed separately for sparse and synthetic projections, showing that the application of the model can significantly improve the reconstruction accuracy of the temperature field of high-energy combustion.

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Section: Introductionmentioning

confidence: 99%

Multi-View Synthesis of Sparse Projection of Absorption Spectra Based on Joint GRU and U-Net

Shi,

Hao,

Huang

et al. 2024

Applied Sciences

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“…Araújo et al proposed a ridge regression method to solve the ill-posed problems in multi-wavelength pyrometry model, and proved the feasibility of this method in improving temperature measurement accuracy (Araújo and Silva, 2020). In the case of little changes in emissivity over the narrow spectral window, a narrow-band spectral window moving temperature inversion algorithm was proposed and validated for multi-wavelength temperature measurement of aero-engine turbine blades, where the relative temperature measurement error was less than 1.33% (Zhao et al, 2021). A cross-validation method was introduced to automatically determine the emissivity model, and a statistical evaluation of temperature measurement accuracy based on this method was performed by Taunay and Choueiri, 2020.…”

Section: Introductionmentioning

confidence: 99%

Measurement performance evaluation and noise compensation for a Fourier transform infrared–based pyrometer

Zhang

et al. 2023

Transactions of the Institute of Measurement and Control

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The Fourier transform infrared (FTIR) spectrometer is widely used for spectrum analysis and radiation intensity measurement. In this work, a pyrometer with the temperature measurement range of 800°C to 1200°C is developed based on the FTIR spectrometer, and the calibration of the instrument coefficients using a standard radiation source is performed. On this basis, the readout noise and shot noise in the spectral signal are analyzed, and a detailed quantitative evaluation of the influences of two kinds of noise on the temperature measurement accuracy is also carried out in this work. Experimental results show that the temperature deviation caused by the two kinds of noise is less than 1°C when the wavelength is within the range of 2.0 to 5.4 μm. However, when the wavelength is greater than 5.4 μm, the maximum temperature deviation caused by the readout noise and shot noise can reach about 12°C and 18°C, respectively. In view of this, a Kalman filter method is introduced in this work to reduce temperature fluctuations caused by these noises, where the maximum fluctuation can be reduced from 83.9°C to 6.1°C with this filter method. These experimental results can provide a valuable guidance for the general-purpose calibration and assessment of the FTIR-based pyrometer.

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“…The least square method was used to realize the accurate measurement of multiwavelength transparent and smooth surface temperature with multi-angle polarization 13 . A narrow-band spectral window moving temperature inversion algorithm was proposed that does not depend on the assumed emissivity model 14 . Xing et al.…”

Section: Introductionmentioning

confidence: 99%

“…13 A narrow-band spectral window moving temperature inversion algorithm was proposed that does not depend on the assumed emissivity model. 14 Xing et al proposed the quadratic measurement iterative cut-off condition optimization algorithm, 15,16 the quadratic measurement algorithm based on constraint optimization, 17,18 and the generalized inverse matrix-exterior penalty function (GIM-EPF) algorithm. 19 The above methods can only be applied to the data processing of a certain kind of materials, and they are not adapt to universal materials.…”

Section: Introductionmentioning

confidence: 99%

Generalized inverse matrix-recurrent neural network data processing algorithm for multiwavelength pyrometer

2022

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A generalized inverse matrix-recurrent neural network (GIM-RNN) data processing algorithm for unknown emissivity was proposed to measure high-temperature by multiwavelength pyrometer (MWP). First, emissivity classification was realized quickly according to a solution from generalized inverse algorithm to underdetermined multiwavelength equation group. According to the relationship between the emissivity of 2 adjacent channels of the 6 channel thermometer used in this paper, 243 emissivity models (1 Ã 3 Ã 3 Ã 3 Ã 3 Ã 3) were designed for classification. Twelve of them were shown on the schematic diagram in the text. To make the figure clear and easy to observe, the prediction results of six common emissivity models were listed as the experimental results. Then, it was input into the corresponding RNN subnetwork to inverse temperature precisely. Simulation results showed that in the range of 1500 to 3000 K temperature, the relative error of the test set was within 1.0% for the network trained after classification by GIM, whereas the relative error of the test set was within 1.2% for the network trained without GIM classification. After 5.0% random noise was added to the inputting data, the relative error still was controlled within 1.5%, which reflected the good antinoise performance of the algorithm. Multispectral measurement data of rocket engine plumes is processed by the proposed algorithm in this manuscript. The inversion results are consistent with the theoretical results. It is indicated that the proposed algorithm has good adaptability to different materials. It is expected to become a general data processing algorithm for MWP.

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Multispectral radiometric temperature measurement algorithm for turbine blades based on moving narrow-band spectral windows

Cited by 20 publications

References 33 publications

Multi-View Synthesis of Sparse Projection of Absorption Spectra Based on Joint GRU and U-Net

Multi-View Synthesis of Sparse Projection of Absorption Spectra Based on Joint GRU and U-Net

Measurement performance evaluation and noise compensation for a Fourier transform infrared–based pyrometer

Generalized inverse matrix-recurrent neural network data processing algorithm for multiwavelength pyrometer

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