Radar data processing of blast furnace stock-line based on spatio-temporal data association

A method of spatio-temporal data association processing based on FMCW radar in blast furnace was proposed in this paper. First, model-categories of basic stock-line profile through mining information of process of production are established. Next, predicting measured value on the basis of historical observations and associating with model category of basic stock-line shape-changing using grey relation algorithm, which acquires the expected distribution values. Finally, Welch FFT and peak-searching method of FT continuous spectrum are researched in the calculation of center distance. Simulation results indicate that the proposed method reduces the average rate of outliers from 13% to 4%, and the matching rate of fitting stock-line associating with prior model class library increases from 68% to 87%, compared with traditional interpolation fitting of direct measurement, which guides the operation of blast furnace charging reasonably.