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Multi-Spectral Temperature Measurement Method Based on Multivariate Extreme Value Optimization |
ZHANG Xuan1, ZENG Chao-bin1, LIU Xian-ya1, CHEN Ping1, 2, 3*, HAN Yan2, 3 |
1. College of Information and Communication Engineering, North University of China, Taiyuan 030051, China
2. Shanxi Key Laboratory of Signal Capturing & Processing, Taiyuan 030051, China
3. State Key Laboratory of Dynamic Testing Technology, North University of China, Taiyuan 030051, China
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Abstract Multispectral thermometry is based on Blackbody radiationlaw, and the temperature value can be calculated based on the radiation intensity and multiple sets of wavelengths. This method has become widely used in engineering practice, as it overcomes the constraints of the single spectrum and similar colorimetric spectrum requirements for colorimetric temperature measurement. In multispectral temperature inversion, the solution of spectral emissivity and multispectral data processing are the keys to accurate temperature measurement. At present, the solution of spectral emissivity is mostly based on the assumption model of spectral emissivity. When the hypothetical model is close to reality, the accuracy of the inverted temperature and spectral emissivity is very high; otherwise, the inversion result deviates significantly. For the temperature measurement of complex materials and the dynamic changes of material properties during the combustion process, the method of assuming the model of spectral emissivity is groundless; In recent years, the deep learning method based on the neural network has been applied to multispectral temperature measurement, which avoids the assumption model of spectral emissivity, and can establish the nonlinear statistical relationship between temperature and multi spectrum, but it requires massive data and supercomputing power support, and the modeling process is complicated.In order to solve the above problems, this paper proposes a multispectral temperature measurement method named multi-element extreme value optimization (MEVO) measurement method. This method utilizes the correlation between multispectral signals at different temperatures, and by analyses the relationship between the measured temperatures of each channel in the process of multispectral temperature inversion, based on the principle of multispectral radiation temperature measurement and the information correlation between the data of each channel in the process of temperature inversion, establish a multivariate temperature difference correlation function, and establish a high-precision temperature measurement model through the optimization of the correlation function. This method simplifies the modeling process to the optimization problem of multivariate temperature difference function, avoids the assumption of the relationship between spectral emissivity and other physical quantities, reduces the requirement of data sample size for deep learning methods, and simplifies the process of multispectral temperature measurement. A simple 8-channel temperature measuring device was used for experimental verification. In the experiment, we determined that the temperature emitted by the Blackbody furnace was the standard value. The spectral data of the 468~603 nm band in the 1 923.15~2 273.15 K temperature zone was calibrated, and the multispectral thermometry based on the optimization of multiple extreme values was realized. The temperature measurement accuracy is about 0.5%, and the temperature inversion time is within 2.5 s. Compared with the second measurement method (SMM) and the neural network method, the inversion accuracy is substantially improved. Moreover, the inversion speed is significantly faster than the SMM method.
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Received: 2022-02-07
Accepted: 2022-05-11
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Corresponding Authors:
CHEN Ping
E-mail: pc0912@163.com
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[1] Araujo A. Infrared Physics & Technology,2016,76:365.
[2] Yu Kun,Guo Huige,Zhang Kaihua,et al. Applied Optics,2021,60(7):1916.
[3] Gao Shan,Zhao Chunhui,Chen Liwei,et al. Measurement Science and Technology,2021,32(5): 055003.
[4] Liang Mei,Sun Bojun,Sun Xiaogang,et al. Measurement,2017,95: 239.
[5] Chen Liwei,Sun Shang,Gao Shan,et al. Infrared Physics and Technology,2020,111: 103523.
[6] QIN Ya-lou,LI Wei,YANG Chun-ping,et al(秦亚楼,李 伟,杨春平,等). Acta Armamentarii(兵工学报),2019,40(1):219.
[7] ZHANG Lei,CHEN Shao-wu,ZHAO Hai-chuan,et al(张 磊,陈绍武,赵海川,等). Chinese Optics(中国光学),2019,12(2):289.
[8] XING Jian,MA Zhao,BAI Yan(邢 键,马 召,白 岩). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2020,40(12):3761.
[9] Zhu Wenjie,Shi Deheng,Zhu Zunlue,et al. International Journal of Heat and Mass Transfer,2017,109:853.
[10] Wang Nian,Shen Hua,Zhu Rihong. Measurement,2020,170: 108725.
[11] Suleiman Fatima K,Lin Kaihsiang,Daun Kyle J. Journal of Quantitative Spectroscopy and Radiative Transfer,2021,271: 107693.
[12] Liu H,Zheng S,Zhou H,et al. Measurement Science & Technology,2016,27(2):025201.
[13] 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.
[14] ZHANG Fu-cai,SUN Xiao-gang,XING Jian, et al(张福才,孙晓刚,邢 键,等). Infrared and Laser Engineering(红外与激光工程),2016,45(7):39.
[15] 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.
[16] XI Jian-hui,JIANG Han,CHEN Bo,et al(席剑辉,姜 瀚,陈 博,等). Journal of Shanghai Jiao Tong University(上海交通大学学报),2021,55(7):891.
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