RESUMEN
Inner wall temperature of ladle is closely related to the quality of steelmaking and control of steel-making tapping temperature. This article adopts a rotating platform to drive an infrared temperature sensor and a laser sensor to scan the temperature field distribution of the ladle inner wall at the hot repair station, where the scanning laser sensor obtains coordinates of each measured point. Because of measuring errors of infrared thermal radiation caused by emissivity uncertainty of the ladle inner wall surface, this article proposes a method for temperature measurement based on Monte Carlo model for effective emissivity correction of each measured point. In the model, we consider the ladle and fire baffle as a cavity. By calculation of the model, the effect of distance from the fire baffle to the ladle and the material surface emissivity of the ladle inner wall on the effective emissivity of the cavity are obtained. After that, the effective emissivity of each measured point is determined. Then the scanning temperature of each measured point is corrected to real temperature. By field measuring test and verification contrast, the results show that: the maximum absolute error of the method in this article is 4.7 °C, the minimum error is 0.6 °C, and the average error is less than 2.8 °C. The method in this article achieves high measurement accuracy and contributes to the control of metallurgical process based on temperature information.
RESUMEN
Massive redundant contours happen when the classical Chan-Vese (C-V) model is used to segment remote sensing images, which have interlaced edges. What's more, this model can't segment homogeneous objects with multiple regions. In order to overcome this limitation of C-V model, narrow band multiple level set method is proposed. The use of N-1 curves is required for the segmentation of N regions and each curve represents one region. First, the level set model to establish an independent multi-region region can eliminate the redundant contours and avoids the problems of vacuum and overlap. Then, narrow band approach to level set method can reduce the computational cost. Experimental results of remote image verify that our model is efficient and accurate.