|
|
|
|
|
|
| Real Temperature Inversion Algorithm for Near-Infrared
Multi-Wavelength Pyrometer Based on Multi Constraint
Optimization Principle |
| ZHANG Fu-cai1, DING Zhi-yu1, SHENG Zi-liang1, SUN Xiao-gang2* |
1. School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China
2. Harbin Institute of Technology, Harbin 150001, China
|
|
|
|
|
Abstract The Multi-wavelength pyrometer is a crucial non-contact temperature measurement instruments that simultaneously detect radiant energy from targets at different wavelengths, enabling real temperature retrieval through data processing. This measurement methodology eliminates physical contact with the measured target, thereby preserving its original thermal characteristics and temperature distribution, making it particularly valuable in high-temperature and ultra-high-temperature applications. The temperature inversion process fundamentally relies on establishing correlations between emissivity and wavelength or radiance temperature. Emissivity, a critical parameter quantifying a radiator's emission capacity relative to blackbody radiation, serves as the bridge connecting real-world radiators with blackbody radiation laws. By determining the emissivity and radiance temperature at specific wavelengths, the real temperature can be computationally derived. Despite decades of international research advancements, two persistent challenges remain: (1) Time-dependent variations in emissivity can lead to significant temperature calculation errors whenever applied models differ from actual conditions; (2) Conventional emissivity-temperature-wavelength relationship models, developed typically through rigorous experimentation and empirical validation, demonstrate limited generalizability and often fail to perform effectively whenever the objects or conditions being measured are altered. The study proposes an innovative emissivity model-independent methodology for rapid real temperature inversion in multi-wavelength pyrometry. By analyzing intrinsic constraints within multi-wavelength measurement theory and integrating them with multi-constraint optimization principles, we developed a novel temperature inversion framework. The approach eliminates traditional dependence on predefined emissivity models while maintaining measurement accuracy. Through rigorous theoretical derivation and experimental validation, we demonstrated the feasibility and universality of this multi-constraint optimization-based method, establishing a new paradigm for multi-spectral pyrometric temperature solutions. This advancement provides enhanced adaptability for diverse measurement scenarios and evolving target characteristics.
|
|
Received: 2025-02-28
Accepted: 2025-07-19
|
|
|
|
Corresponding Authors:
SUN Xiao-gang
E-mail: sxg@hit.edu.cn
|
|
[1] Yang C B, Ezendeeva D, Yu T, et al. Optics Express, 2021, 29(21): 33234.
[2] Gao S, Zhao C, Chen L, et al. Measurement Science and Technology, 2021, 32(5): 055003.
[3] Dieter K, Koschnick K, Lill J, et al. Journal of Quantitative Spectroscopy and Radiative Transfer, 2022, 277: 107978.
[4] Guiberti T F, Krishna Y, Boyette W R, et al. Proceedings of the Combustion Institute, 2021, 38(1): 1647.
[5] Yu K, Guo H, Zhang K, et al. Applied Optics, 2021, 60(7): 1916.
[6] Trabold J, Butz D, Schneider S, et al. Combustion and Flame, 2022, 243: 111864.
[7] ZHAO Yu-qing，LI Jian-qiang，SHENG Peng，et al(赵玉清，李建强，盛 鹏，等). Journal of Ordnance Equipment Engineering(兵器装备工程学报），2021，42(11)：146.
[8] SUN Hong-sheng，LIANG Xin-gang，MA Wei-gang, et al(孙红胜，梁新刚，马维刚，等). Infrared and Laser Engineering(红外与激光工程），2021，50(5)：36.
[9] XI Jian-hui，JIANG Han，CHEN Bo，et al(席剑辉，姜 瀚，陈 博，等). Journalof Shanghai JiaoTong University(上海交通大学学报），2021，55(7)：891.
[10] ZHANG Ning-chao，YE Xin，LI Duo, et al(张宁超, 叶 鑫, 李 多, 等). Spectroscopy and Spectral Analysis（光谱学与光谱分析），2023，43(12): 3666.
[11] DU Pei-jun，ZHANG Wei，ZHANG Peng，et al(杜培军，张 伟，张 鹏，等). Acta Geodaetica et Cartographica Sinica（测绘学报)，2023，52(7)：1090.
|
| [1] |
YUAN Bo. An Improved NSGA-Ⅲ Algorithm of Information-Redundancy
Bi-Objective Optimization for Hyperspectral Band Selection[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(12): 3524-3532. |
| [2] |
ZHU Ting-ting1, PAN Cong-yuan1, 2, 3*, ZHAO Qian-jin1, XUE Hua-qin2, 3, SHEN Yuan2, 3, ZHANG Bing2, 3. Research on a Genetic Algorithm-Optimized XGBoost Algorithm for
Quantitative Analysis of Coal Quality Using Laser-Induced
Breakdown Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(11): 3048-3056. |
| [3] |
MAO Xiao-dong, HUANG Zhi-kai, LIU Yan-de, HU Jun*. Highly Sensitive Detection Method for Trace Paclobutrazol Residues Based on Terahertz Metamaterial Resonant Enhancement Combined With
ECO-SVR[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(11): 3081-3089. |
| [4] |
ZHANG Meng-fan1, LI Mao-gang1*, LIU Yi-jiang1, YAN Chun-hua1, ZHANG Tian-long2, LI Hua1, 2*. Rapid Quantitative Analysis of Trace Elements in Petroleum Coke by LIBS Combined With Whale Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(10): 2796-2803. |
| [5] |
ZHANG Fu1, 2, LIU Zhi-hua1, YAN Bao-ping1, WANG Jia-jia3, FU San-ling4*. Research on Noise Reduction Method for TDLAS Signal Detection Based on BOA-VMD-AWTD Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(10): 2915-2921. |
| [6] |
CUI Shuang-long, ZHOU Yi-meng, XING Jian*, LI Yi, LI Wen-chao, HE Xue-lan. Simulation Study on the Influence of Microstructured Arrays on the
Emissivity of Surface Blackbody[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(10): 2922-2929. |
| [7] |
ZHANG He, GAO Kun*, KE Kun-xin, WANG Jing-yi, ZHANG Ze-feng, HU Bai-yang, YANG Ji-yuan, CHENG Hao-bo. Reference-Free Reconstruction of Hyperspectral Reflectance Under Complex Illumination Based on Multi-Level Cyclic Optimization Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(08): 2174-2182. |
| [8] |
JIN Hua-wei1, 2, 3, TANG Yu-hao2, SHI Jia-sheng2, FANG Lei2, LIU Wen-jian3. Design and Optimization of H-Type Resonant Photoacoustic Cell for
Composite Buffer Cavity[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(06): 1521-1526. |
| [9] |
MA Jia-hao1, YANG Jian-bo1, 2*, LI Rui1, XU Jie2, LI Hui2, WU Jia-hui2. Application of Solid-Liquid Mixing Sample Preparation With Standard Addition Method in EDXRF Detection of Heavy Metal Content in Soybeans[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(06): 1639-1647. |
| [10] |
ZHANG Jia-lun1, 2, ZHANG Wei-gang2*, ZHUANG Yue-ting1, 2, ZHANG Qian-feng1. Construction and Performance Control of Low Infrared Emissivity
Coating Based on Visible and Near-Infrared Reflectance Spectra
of Green Vegetation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(06): 1663-1669. |
| [11] |
CHEN Zhuo-ting1, WANG Qiao-hua1, 2*, WANG Dong-qiao1, CHEN Yan-bin1, LI Shi-jun1, 2. Non-Destructive Detection of Pre-Incubation Breeding Duck Egg Fertilization Information Based on Visible/Near Infrared Spectroscopy and Joint Optimization Strategy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(05): 1469-1475. |
| [12] |
TIAN Fu-chao1, 2, 3, ZHANG Hai-long1, 2, 3, SU Jia-hao1, 2, 3*, LIANG Yun-tao1, 2, 3, WANG Lin1, 2, 3, WANG Ze-wen1, 2, 3. Pressure Compensation of Industrial Ambient Gases and Their Prediction Based on Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(04): 994-1007. |
| [13] |
LIU Xue-jing1, CUI Hong-shuai1, YIN Xiong1, MA Shi-yi1, ZHOU Yan1*, CHONG Dao-tong1, XIONG Bing2, LI Kun2. A Study on the Detection of Wear Particle Content of Lubricating Oil Based on Reflectance Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(03): 826-835. |
| [14] |
ZHANG Guo-hao1, WANG Cai-ling1*, WANG Hong-wei2*, YU Tao3. Improved Particle Swarm Optimization Algorithm Combined With BP Neural Network Model for Prediction of Total Phosphorus Concentration in Water Body Using Transmittance Spectral Data[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(02): 394-402. |
| [15] |
XIAO Zhong-liang, YUAN Rong-yao, FU Zhuang, LIU Cheng, YIN Bi-lu, XIAO Min-zhi, ZHAO Ting-ting, KUANG Yin-jie, SONG Liu-bin*. Study on the Aging Behavior of Transformer Oil Based on Machine
Learning and Infrared Spectroscopy Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(02): 434-442. |
|
|
|
|
