Radar Detection-based Modeling in a Blast Furnace: a Prediction Model of Burden Surface Shape after Charging

Abstract

Radar detection is an advanced method for monitoring a blast furnace's inner burden surface shape, which is an important factor that largely affects the production efficiency of the iron-making process. In this paper, a radar detection-based model for the prediction of burden surface shape was developed for assisting operators in developing a charging strategy. The data used are composed of both the detection and controlling records of a real, working-state blast furnace obtained by mechanical swing radar and a furnace database system, respectively. By defining and analyzing the stacking density function, the physical meanings of the modeling principles were revealed. Combined with the classical force charging trajectory sub-model and detection-driven burden descent calculation, the proposed model adopts Gaussian radius basis functions to approximate the stacking mechanism of the burden charging process. The parameter identification results show that the model can approximate the burden surface radius profile well. Compared with the results obtained for coke layers, the parameters' ranges for the ore layers are narrower. Performance comparison shows that the proposed model has the advantages of higher prediction accuracy for both local details and global shape over the classical polygonal line model.

Tracking the Burden Surface Radial Profile of a Blast Furnace by a B-mode Mechanical Swing Radar System

“…Developed on a common basis with the 6-point array radar system, 10) the mechanical swing radar (MSR) system detects the burden surface shape by scanning the burden surface radius through the antenna's periodic swing. [12][13][14] Since the sampling positions of the surface height are more densely placed on the same burden surface radius, the approximated burden surface shape is more precise compared to the 6-point array radar system.…”

“…In Eqs. (11) and (12), Q specifies the number of the subdivided transmitting direction of the radar wave within the beamwidth. We refer to Y θ = {y j } M×Q as a beam matrix at the direction θ of the antenna.…”

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

“…Two main factors that affect the BSRP directly are burden charging and burden descending. Modeling of the charging process and burden stacking behavior has been addressed in our previous research [3]. As a continuation of the previously established model, a model of the descent speed distribution along the burden surface radius (BSRD) is proposed in this research.…”

“…In our former work, a prediction model of burden charging was constructed [3]. In this research, a kinematic modeling-based prediction model of BSRD was proposed.…”

A Real-Time 3D Measurement System for the Blast Furnace Burden Surface Using High-Temperature Industrial Endoscope

“…Several pointwise methods have been employed to gauge the BF burden surface [5][6][7][8][9]. Direct detection methods for shape measurement of the BF burden surface mainly employ mechanical probes, radar probes, laser probes, and infrared imagers.…”