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Until now, the air temperature sensors inside thermometer screens and radiation shields are affected by solar radiation, which causes the measuring result to become greater than the actual temperature. The temperature rise can reach 0.8 K or even higher. In this paper, a temperature sensor array design is established for obtaining high precision measurement results. The temperature sensor array consists of an array of radiation shields which features a tube-shape, a platinum resistance sensor array, an aluminum plate with a silver mirror surface and a temperature measurement module that includes a high accuracy thermometer circuit. There is always at least one radiation shield that supplies relatively good ventilation under any airflow direction. A computational fluid dynamic method is implemented to analyze and calculate the temperature rise induced by radiation under various environmental conditions. A correction equation of the temperature rise is obtained by surface fitting using a genetic algorithm. The measurement accuracy can be further improved by this correction equation. In order to verify the performance of the sensor array, a forced ventilation temperature measurement platform is constructed, which consists of a platinum resistance sensor, an L-shaped radiation shield and an air pump. The airflow rate inside the radiation shield can be up to 20~m/s, and the L-shaped radiation shield can horizontally rotate under the control of a software to minimize the error caused by the heated radiation shield. The temperature sensor array, a temperature sensor with traditional radiation shield, and the forced ventilation temperature measurement platform are characterized in the same environment. To experimentally verify the computational fluid dynamic method and the genetic algorithm, a number of contrast tests are performed. The average temperature rise of sensors equipped with the traditional radiation shields is 0.409 K. In contrast, the temperature rise of the sensor array is as low as 0.027K. This temperature sensor array allows the error caused by solar radiation to be reduced by a percentage of approximately 93%. The temperature rise of temperature sensor array, caused by the angular variation of airflow direction is on the order of several mK. When the solar radiation intensity and the airflow rate are 1000W/m2 and 0.1m/s, respectively, the temperature rise is 0.097 K. The temperature rise is 0.05K, when the airflow rate is greater than 0.4 m/s. The temperature rise can be reduced to 0.01 K, when the airflow rate is greater than 2 m/s. The average offset and root mean square error between the correction equation and experimental results are 0.0174 K and 0.0215 K, respectively, which demonstrates the accuracy of the computational fluid dynamic method and genetic algorithm proposed in this research. The temperature measurement accuracy has the potential to be further improved by utilizing the computational fluid dynamics method and the genetic algorithm.
[1] Dai X G, Liu Y, Wang P 2015 Chin. Phys. B 24 049201
[2] Toggweiler J R, Joellen R 2008 Nature 451 286
[3] Joan B, Oller J M, Huey R B, Gilchrist G W, Luis S 2007 Science 315 1497
[4] Kerr R A 2011 Science 334 173
[5] Wang X J, Zhi R, He W P, Gong Z Q 2012 Chin. Phys. B 21 029201
[6] Qian Z H, Hu J G, Feng G L, Cao Y Z 2012 Chin. Phys. B 21 109203
[7] Dillon M E, George W, Huey R B 2010 Nature 467 704
[8] Wigley T M, Jones P D, Raper S C 1997 Proc. Natl. Acad. Sci. USA 94 8314
[9] Lin X, Hubbard K G, Walter-Shea E A, Brandle J R, Meyer G E 2001 J. Atoms. Ocean. Tech. 18 1470
[10] Lin X 1999 Ph. D. Dissertation (Lincoln: University of Nebraska)
[11] Lin X, Hubbard K G, Walter-Shea E A 2001 J. Atoms. Ocean. Tech. 44 1299
[12] Thomas C K, Smoot A R 2013 J. Atoms. Ocean. Tech. 30 526
[13] Richardson S J, Brock F V, Semmer S R, Jirak C 1999 J. Atoms. Ocean. Tech. 16 1862
[14] Holden Z A, Klene A E, Keefe R F, Moisen G G 2013 Arg. Forest. Meteorol. 180 281
[15] Lopardo G, Bertiglia F, Curci S, Roggero G, Merlone A 2014 Int. J. Climatol. 34 1297
[16] Hubbart J, Link T, Campbell C, Cobos D 2005 Hydrol. Process. 19 1517
[17] Georges C, Kaser G 2002 J. Geophys. Res. 107 ACL 15-1
[18] Erell E, Leal V, Maldonado E 2005 Bound-Lay. Mmteorol. 114 205
[19] Nakamura R, Mahrt L 2005 J. Atmos. Ocean. Tech. 22 1046
[20] Wang X L, Han Y J 2008 Meteorological, Hydrological and Marine Instruments 2 68 (in Chinese) [王晓蕾, 韩有君 2008 气象水文海洋仪器 2 68]
[21] Chen F Z, Qiang H F, Gao W R 2014 Acta Phys. Sin. 62 230206 (in Chinese) [陈福振, 强洪夫, 高巍然 2014 62 230206]
[22] Jiang Y M, Liu Y 2013 Acta Phys. Sin. 62 204501 (in Chinese) [蒋亦民, 刘佑 2013 62 204501]
[23] Mao X L, Xiao S R, Liu Q Q, Li M, Zhang J H 2014 Acta Phys. Sin. 63 144701 (in Chinese) [冒晓莉, 肖韶荣, 刘清惓, 李敏, 张加宏 2014 63 144701]
[24] Wang F J 2004 Computational Fluid Dynamics: Principle and Application of CFD Software 1 (Beijing: Tsinghua University Press) pp6-7 (in Chinese) [王福军 2004 计算流体动力学分析-CFD软件原理与应用1(北京: 清华大学出版社)第6-7页]
[25] Anderson J D (translated by Wu S P, Liu Z S) 2010 Computational Fluid Dynamics: The Basics with Applications (Beijing: China Machine Press) pp179-180 (in Chinese) [约翰D安德森 著(吴颂平, 刘赵森 译) 2010 计算流体力学基础及其应用(北京: 机械工业出版社)第179-180页]
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[1] Dai X G, Liu Y, Wang P 2015 Chin. Phys. B 24 049201
[2] Toggweiler J R, Joellen R 2008 Nature 451 286
[3] Joan B, Oller J M, Huey R B, Gilchrist G W, Luis S 2007 Science 315 1497
[4] Kerr R A 2011 Science 334 173
[5] Wang X J, Zhi R, He W P, Gong Z Q 2012 Chin. Phys. B 21 029201
[6] Qian Z H, Hu J G, Feng G L, Cao Y Z 2012 Chin. Phys. B 21 109203
[7] Dillon M E, George W, Huey R B 2010 Nature 467 704
[8] Wigley T M, Jones P D, Raper S C 1997 Proc. Natl. Acad. Sci. USA 94 8314
[9] Lin X, Hubbard K G, Walter-Shea E A, Brandle J R, Meyer G E 2001 J. Atoms. Ocean. Tech. 18 1470
[10] Lin X 1999 Ph. D. Dissertation (Lincoln: University of Nebraska)
[11] Lin X, Hubbard K G, Walter-Shea E A 2001 J. Atoms. Ocean. Tech. 44 1299
[12] Thomas C K, Smoot A R 2013 J. Atoms. Ocean. Tech. 30 526
[13] Richardson S J, Brock F V, Semmer S R, Jirak C 1999 J. Atoms. Ocean. Tech. 16 1862
[14] Holden Z A, Klene A E, Keefe R F, Moisen G G 2013 Arg. Forest. Meteorol. 180 281
[15] Lopardo G, Bertiglia F, Curci S, Roggero G, Merlone A 2014 Int. J. Climatol. 34 1297
[16] Hubbart J, Link T, Campbell C, Cobos D 2005 Hydrol. Process. 19 1517
[17] Georges C, Kaser G 2002 J. Geophys. Res. 107 ACL 15-1
[18] Erell E, Leal V, Maldonado E 2005 Bound-Lay. Mmteorol. 114 205
[19] Nakamura R, Mahrt L 2005 J. Atmos. Ocean. Tech. 22 1046
[20] Wang X L, Han Y J 2008 Meteorological, Hydrological and Marine Instruments 2 68 (in Chinese) [王晓蕾, 韩有君 2008 气象水文海洋仪器 2 68]
[21] Chen F Z, Qiang H F, Gao W R 2014 Acta Phys. Sin. 62 230206 (in Chinese) [陈福振, 强洪夫, 高巍然 2014 62 230206]
[22] Jiang Y M, Liu Y 2013 Acta Phys. Sin. 62 204501 (in Chinese) [蒋亦民, 刘佑 2013 62 204501]
[23] Mao X L, Xiao S R, Liu Q Q, Li M, Zhang J H 2014 Acta Phys. Sin. 63 144701 (in Chinese) [冒晓莉, 肖韶荣, 刘清惓, 李敏, 张加宏 2014 63 144701]
[24] Wang F J 2004 Computational Fluid Dynamics: Principle and Application of CFD Software 1 (Beijing: Tsinghua University Press) pp6-7 (in Chinese) [王福军 2004 计算流体动力学分析-CFD软件原理与应用1(北京: 清华大学出版社)第6-7页]
[25] Anderson J D (translated by Wu S P, Liu Z S) 2010 Computational Fluid Dynamics: The Basics with Applications (Beijing: China Machine Press) pp179-180 (in Chinese) [约翰D安德森 著(吴颂平, 刘赵森 译) 2010 计算流体力学基础及其应用(北京: 机械工业出版社)第179-180页]
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