Radar Detection-Based Modeling in a Blast Furnace: A Prediction Model of Burden Surface Descent Speed

Abstract

The distribution of burden layers is a vital factor that affects the production of a blast furnace. Radars are advanced instruments that can provide the detection results of the burden surface shape inside a blast furnace in real time. To better estimate the burden layer thicknesses through improving the prediction accuracy of the burden descent during charging periods, an innovative data-driven model for predicting the distribution of the burden surface descent speed is proposed. The data adopted were from the detection results of an operating blast furnace, collected using a mechanical swing radar system. Under a kinematic continuum modeling mechanism, the proposed model adopts a linear combination of Gaussian radial basis functions to approximate the equivalent field of burden descent speed along the burden surface radius. A proof of the existence and uniqueness of the prediction solution is given to guarantee that the predicted radial profile of the burden surface can always be calculated numerically. Compared with the plain data-driven descriptive model, the proposed model has the ability to better characterize the variability in the radial distribution of burden descent speed. In addition, the proposed model provides prediction results of higher accuracy for both the future surface shape and descent speed distribution.

Development and Implementation of Decision Support Systems for Blast Smelting Control in the Conditions of PrJSC “Kamet-Steel”

“…In addition to preliminary studies, it is necessary to equip BFs with additional means (systems) for monitoring process parameters. Such important and promising means of control for Ukraine include the following: means of temperature control of the gas flow over the burden surface [14][15][16], radar means for monitoring the configuration of the burden surface [17][18][19], means for controlling the distribution of the chemical composition of gases along the radius of the BF above the burden surface and (or) in the upper zone of the BF [20], control of blast distribution for each air tuyere, and multi-point control of static pressure along the height of the BF shaft [21].…”

“…BF charging control is an important element in controlling the operation of a BF and achieving high technical and economic indicators. Literature analysis reveals a variety of mathematical models used to assist in the distribution of charge materials, using discrete element modeling [37][38][39][40][41], experiments on physical models [40][41][42], dynamic clustering method based on dynamic time deformation and adaptive resonance theory, charge distribution control based on the inverse dynamic model [43], other methods of calculation and forecasting [43], and known methods based on radar technology [17][18][19]44] to determine the surface of the charge. To implement the third DSS for adjusting the parameters of the charging mode, it is proposed to use information on the dynamics of changes in the temperatures of the gas flow above the charge surface.…”

A Mathematical Model Combined with Radar Data for Bell-Less Charging of a Blast Furnace

“…Tian et al[18] developed a radar detection-based model for the prediction of the burden surface shape to develop a charging strategy and the results showed that the proposed model had the advantages of higher prediction accuracy for both local details and global shape than mechanical stock rods. In another publication [19], they proposed an innovative data-driven model for predicting the distribution of the burden descent speed. This model has the ability to better characterize the variability in the radial distribution of the burden descent speed than a pure mathematical model based on Newton's second law.…”