Colorimetric Temperature Measurement Algorithm Based on Multi-Sensor Data Fusion

Article Preview

Abstract:

Wavelength and other factors have a deep influence on temperature measurement system based on CCD image sensor. Deviations between measurement values sometimes are large. In order to reduce error, the temperature outputs in different wavelength combinations do have multi-sensor correlation properties in point of colorimetric temperature measurement system view. The colorimetric temperature measurement algorithm based on real-time adaptive weighted is put forward by such performance index that minimum of standard deviation. According to measured value of each sensor, we will find out the corresponding weights in adaptive manner. And discuss the statistical properties of the estimated standard deviation. Estimation unbiasedness is proved. The algorithm has the following advantages .A much smaller amount of calculation, without any a priori knowledge, only relying on the output of each sensor. All of these make temperature estimation be optimal, measurement accuracy and the real-time performance of the system are improved. Theoretical analysis and experimental results show that the colorimetric temperature measurement algorithm based on the real-time adaptive weighted improves obviously when comparing with the traditional means algorithm in measurement accuracy.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

146-150

Citation:

Online since:

February 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Wang Kuihan, Li You, Wang Baizhong. Process Automation Instrumentation, Vol. 22 No. 8, (2001), pp.1-7.

Google Scholar

[2] Sun Yuan, Peng Xiaoqi, Tang Ying. Chinese Journal of Scientific Instrument, Vol. 29 No. 1, (2008), pp.49-54.

Google Scholar

[3] B. Muller, U. Renz. Review of Scientific Instrument, Vol. 72 No. 8, (2001), pp.3366-3374.

Google Scholar

[4] Luo R. C. Chih chen Yih, Kuo Lan Su. Sensor Journal IEEE, Vol. 2 No. 2, (2002), pp.107-109.

Google Scholar

[5] Gunho Sohn, Ian Dowman. Journal of Photogrammetry and Remote Sensing, Vol. 62 No. 1, (2007), pp.43-63.

Google Scholar

[6] G. Kychakoff, A. F. Hollingshead, S. P. Boyd. Cement Industry Technical Confernence. Kansas City, (2005).

Google Scholar