Simulation Approach to Temperature Measuring Using Image Color Based on Support Vector Regression

Authors

Ren Yan, School of Automation, Shenyang Aerospace University, Shenyang 110136, China;
Xiaomin Zhou, School of Automation, Shenyang Aerospace University, Shenyang 110136, China;
Guan Wei, School of Automation, Shenyang Aerospace University, Shenyang 110136, China;
Fu Li, School of Automation, Shenyang Aerospace University, Shenyang 110136, China;
Xinyu Chen, School of Automation, Shenyang Aerospace University, Shenyang 110136, China;

Abstract

Abstract: As it is all known, it is difficult to measure high temperature directly in complex industrial environment. Thus, a new temperature soft-measuring method based on Support Vector Regression (SVR) was proposed. SVR model was used to fit the complex nonlinear mapping relationship between the feature values of color images of the high temperature object and its temperature. And then the trained model could predict the temperature by inputting the features of colorimages. Simulation results demonstrate that the improved algorithm has excellent generalization ability and predictive ability. What’s more, this model needs less support vectors and learns faster.

Recommended Citation

Yan, Ren; Zhou, Xiaomin; Wei, Guan; Li, Fu; and Chen, Xinyu (2020) "Simulation Approach to Temperature Measuring Using Image Color Based on Support Vector Regression," Journal of System Simulation: Vol. 28: Iss. 11, Article 13.
DOI: 10.16182/j.issn1004731x.joss.201611013
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss11/13

First Page

2736

Revised Date

2015-05-18

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201611013

Last Page

2741

CLC

TN.219

Recommended Citation

Ren Yan, Zhou Xiaomin, Guan Wei, Fu Li, Chen Xinyu. Simulation Approach to Temperature Measuring Using Image Color Based on Support Vector Regression[J]. Journal of System Simulation, 2016, 28(11): 2736-2741.

DOI

10.16182/j.issn1004731x.joss.201611013