主催: 日本エネルギー学会, 石炭科学部会, コークス工学研究部会, 重質油部会
共催: 石炭・炭素資源有効利用研究会
会議名: 第59回石炭科学会議
開催地: 札幌・道民活動センターかでる2.7（ハイブリッド開催）
開催日: 2022/10/20 - 2022/10/21
p. 50-51
In order to predict the trajectory of ash particles as they impact the heat transfer tubes due to inertial impact, information on particle size, density, and particle shape of ash particles is necessary. In this study, we investigated a method for shape classification of ash particles using deep learning from SEM images of fly ash particles. As a result, we succeeded in classifying ash particles ranging in size from 1 to 200 μm into eight shapes and obtaining an integrated particle size distribution for each shape.
