Inner Wall Temperature Distribution Measurement of The Ladle Based on Cavity Effective Emissivity Correction

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℃, the minimum error is 0.6℃, and the average error is less than 2.8℃. The method in this article achieves high measurement accuracy and contributes to the control of metallurgical process based on temperature information.

Prediction of the Emissivity Curve at High Temperatures of Low Carbon Steel

The thermography is an attractive technique to record the real-time temperature during the continuous welding processes. The temperature distribution during the weld zone is essential for understanding and evaluating the metallurgical properties of the joints. The knowledge of the material emissivity curve is necessary for the precise acquisition of thermography data. This emissivity value is usually assumed constant in the thermography software data acquisition, resulting in inaccurate thermographic data. The surface emissivity usually depends on the temperature. Thus, the values obtained in the literature may not be valid for materials of interest under the process’s conditions. Especially in the case of the low carbon steels, the emissivity data available are scarce and frequently obtained at low temperatures (below 200oC). Therefore, we proposed a methodological procedure to measure the effective surface emissivity, which considers the effect of temperatures and surface conditions. This research was focused on the development of an experimental methodology for determining the emissivity curve, using as the sample, a low carbon steel (0.07% C) with 0.21 mm thickness obtained from the productive stock of a continuous annealing line in the steel plant of the Companhia Siderúrgica Nacional (CSN). The normal sample emissivity was evaluated in the temperature range from 100ºC to 800ºC. It was proposed a model based on a sigmoid function to represent the effective emissivity during temperature rise. The sigmoid model parameters were obtained by a fitting procedure using temperature measurements obtained by thermocouples. The results showed an effective emissivity variation as a function of temperature, where emissivity values raged in the interval of 0.09 to 0.83. Thus, the useful emissivity curve was used to correct the thermography data obtained in electrical resistance seam welding (RSEW) with three levels of heats inputs. The correlation for the emissivity curve incorporated in the thermography software was applied to the thermal profiles of the welds analyzed from 441ºC to 713ºC. These values are consistent with the welding process used. The developed methodology can be applied, in a similar way, in the correction of profiles in other types of welding processes.

A Monte Carlo Emissivity Model for Wind-Roughened Sea Surface

Sea surface emissivity (SSE) is a key variable in the estimation of sea surface temperature and the sea surface radiation budget. A physical base SSE model with adequate accuracy and acceptable computational efficiency is highly desired. This paper develops a Monte Carlo ray-tracing model to compute the SSE of a wind-roughened sea surface. The adoption of a two-dimensional continuous surface model and averaging the two polarization components in advance before ray-tracing gives the model acceptable computational efficiency. The developed model can output the contributions of direct emission and the reflected component to the effective emissivity. The contribution of the reflected component to the effective emissivity reaches 0.035 at an 80° emission angle for a wind speed larger than 10 m/s. The emissivity spectra and channel emissivities collected from two field campaigns and one set of outdoor measurements are used to validate the developed model. Statistical results indicate that the absolute value of bias or difference is less than 0.5% when the view angle is less than 65°, which means the retrieval accuracy of sea surface temperature (SST) is guaranteed from the view of SSE. When the view angle increases, the accuracy of the developed model degraded, especially at the view angle of 85°. Without considering this view angle, the absolute value of bias or difference is less than 0.016, and the root mean square difference (RMSD) is less than 0.018.

Cloud Effective Emissivity Retrievals Using Combined Ground-Based Infrared Cloud Measuring Instrument and Ceilometer Observations

In this paper, a new inversion procedure for cloud effective emissivity retrievals using a combined ground-based infrared cloud measuring instrument with ceilometer was developed. A quantitative sensitivity and performance analysis of the proposed method was also provided. It was found that the uncertainty of the derived effective emissivity was mainly associated with errors on the measurement radiance, the simulated radiance of clear sky and blackbody cloudy sky. Furthermore, the retrieval at low effective emissivity was most sensitive to the simulated clear sky radiances, whereas the blackbody cloudy sky radiance was the prevailing source of uncertainty at high emissivity. This newly proposed procedure was applied to the measurement taken in the CMA Beijing Observatory Station from November 2011 to June 2012 by the whole-sky infrared cloud-measuring system (WSIRCMS) and CYY-2B ceilometer. The cloud effective emissivity measurements were in good agreement with that of the MODIS/AQUA MYD06 Collection 6 (C6) cloud products. The mean difference between them was 0.03, with a linear correlation coefficient of 0.71. The results demonstrate that the retrieval method is robust and reliable.