Influence of Dust on Temperature Measurement Using Infrared Thermal Imager

被引:15
作者
Pan, Dong [1 ]
Jiang, Zhaohui [1 ]
Gui, Weihua [1 ]
Maldague, Xavier [2 ]
Jiang, Ke [1 ]
机构
[1] Cent South Univ, Sch Automat, Changsha 410083, Peoples R China
[2] Univ Laval, Dept Elect & Comp Engn, Quebec City, PQ G1V 0B1, Canada
基金
中国国家自然科学基金;
关键词
Temperature measurement; Optical variables measurement; Thermal lensing; Furnaces; Adaptive optics; Optical imaging; Lenses; Compensation; dust; infrared thermography; temperature measurement; THERMOGRAPHY; ANGLE; VIEW;
D O I
10.1109/JSEN.2019.2957064
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Temperature measurement by infrared thermal imager is an attractive technique in many fields, and it is of great importance to ensure the measurement accuracy of the infrared thermal imager. Aiming at the influence of dust on the temperature measurement of infrared thermal imager, this paper summarized the dust influence into three categories: dust on the surface of the measured object, dust on the infrared thermal imager's lens and dust in the optical path between the measured object and the infrared thermal imager, and conducted three dust experiments. To quantify the measurement errors caused by dust, the infrared thermal image features that are affected by dust are extracted and a compensation model is established based on polynomial regression. The results indicate that dust can introduce measurement errors of infrared thermal imager and the proposed compensation method can compensate for the measurement errors caused by dust and improve the accuracy of infrared thermal imager.
引用
收藏
页码:2911 / 2918
页数:8
相关论文
共 21 条
[1]   Infrared thermography for condition monitoring - A review [J].
Bagavathiappan, S. ;
Lahiri, B. B. ;
Saravanan, T. ;
Philip, John ;
Jayakumar, T. .
INFRARED PHYSICS & TECHNOLOGY, 2013, 60 :35-55
[2]   Self-Calibrating Infrared Thermometer for Low-Temperature Measurement [J].
Barry, Tim ;
Fuller, Gary ;
Hayatleh, Khaled ;
Lidgey, John .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2011, 60 (06) :2047-2052
[3]   Recognition of the Temperature Condition of a Rotary Kiln Using Dynamic Features of a Series of Blurry Flame Images [J].
Chen, Hua ;
Zhang, Xiaogang ;
Hong, Pengyu ;
Hu, Hongping ;
Yin, Xiang .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2016, 12 (01) :148-157
[4]   Influence of environmental factors on infrared eye temperature measurements in cattle [J].
Church, J. S. ;
Hegadoren, P. R. ;
Paetkau, M. J. ;
Miller, C. C. ;
Regev-Shoshani, G. ;
Schaefer, A. L. ;
Schwartzkopf-Genswein, K. S. .
RESEARCH IN VETERINARY SCIENCE, 2014, 96 (01) :220-226
[5]   Study on high-precision temperature measurement of infrared thermal imager [J].
Dai, Shao-sheng ;
Yan, Xiao-hui ;
Zhang, Tian-qi .
INFRARED PHYSICS & TECHNOLOGY, 2010, 53 (05) :396-398
[6]   Temperature measurement of molten iron in taphole of blast furnace combined temperature drop model with heat transfer model [J].
Jiang, Z. H. ;
Pan, D. ;
Gui, W. H. ;
Xie, Y. F. ;
Yang, C. H. .
IRONMAKING & STEELMAKING, 2018, 45 (03) :230-238
[7]   Compensation method for the influence of angle of view on animal temperature measurement using thermal imaging camera combined with depth image [J].
Jiao, Leizi ;
Dong, Daming ;
Zhao, Xiande ;
Han, Pengcheng .
JOURNAL OF THERMAL BIOLOGY, 2016, 62 :15-19
[8]   Medical applications of infrared thermography: A review [J].
Lahiri, B. B. ;
Bagavathiappan, S. ;
Jayakumar, T. ;
Philip, John .
INFRARED PHYSICS & TECHNOLOGY, 2012, 55 (04) :221-235
[9]   Flame Image-Based Burning State Recognition for Sintering Process of Rotary Kiln Using Heterogeneous Features and Fuzzy Integral [J].
Li, Weitao ;
Wang, Dianhui ;
Chai, Tianyou .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2012, 8 (04) :780-790
[10]   Influence of Angle of View on Temperature Measurements Using Thermovision Camera [J].
Litwa, Mariusz .
IEEE SENSORS JOURNAL, 2010, 10 (10) :1552-1554