QUALITY CONTROL OF STEEL HEATING IN FURNACES BY THE SURFACE TEMPERATURE OF BLANKS IN THE LANGUISHING ZONE

Abstract

Introduction. In the conditions of increasing requirements for the quality of metal heating before rolling, the task of improving the algorithmic support of automated process control systems (APCS) of heating furnaces is quite relevant. Purpose of the study. The article considers a solution to the problem of monitor-ing the temperature difference across the cross-section of blanks based on the rate of change of their surface temperature in the soaking zones of continuous furnaces. It is shown that the use of such an approach makes it possible, in principle, to exclude the influence of the surface scale layer on the accu-racy of assessing the controlled parameter. Materials and methods. An analysis of literary sources was performed and a generalization of the known results on the problem of differentiating industrial signals was carried out. The following tested options for solving this problem are highlighted: 1) with preliminary ap-proximation of the measured data by a certain function; 2) direct multi-point digital differentiation. Re-sults. The conditions for the applicability of both the first and second options for solving the problem of monitoring the temperature difference in the soaking zones of continuous furnaces were established. Specifically, a four-point digital slab surface temperature differentiator was used. For greater accuracy of temperature drop estimation, it was envisaged to include a preliminary filtering algorithm in the digital processing scheme of experimental data. The filtering algorithm was found from the solution of the optimization problem; it was noted that this algorithm is similar in structure to the filtering algorithms constructed according to the well-known approaches of R. Kalman. The results of computational experiments are presented. It is shown that prelim-inary filtering significantly increases the accuracy of parameter estimation by the digital differentiation method. Conclusion. The results of the work can be used to improve the algorithmic support of the automated process control system of continuous furnaces.