APPARATUS AND METHOD FOR MONITORING PARTICLE SIZE OF RAW MATERIALS OF BLAST FURNACE

The purpose of the present invention is to provide an apparatus and a method for assessing the particle size of a blast furnace raw material, wherein individual particles of a raw material are detected from a video image captured to assess the particle size of the raw material, and the type of the raw material is simultaneously identified, thereby assessing the particle size with regard to each raw material type. A video acquisition unit acquires continuous videos of raw materials transferred to a blast furnace. An assessment unit identifies the type of raw materials according to the boundary of respective raw materials and the surface color and pattern of respective raw materials, based on the difference in brightness of raw material images included in the videos, by using a preconfigured deep learning algorithm. The representative size value of raw material individual particles is determined by using size information based on the number of pixels occupied by raw material individual particles in the raw material images. In addition, the assessment unit calculates the average particle size of all raw materials according to the determined representative size value of raw material individual particles, and calculates the particle size with regard to each raw material type according to the raw material type distinguished according to the deep learning algorithm.