Blasted rock material serves a critical role in various engineering
applications, yet the phenomenon of segregation-where particle sizes vary
significantly along the gradient of a quarry pile-presents challenges for
optimizing quarry material storage and handling. This study introduces an
advanced image analysis methodology to characterize such segregation of rock
fragments. The accurate delineation of detailed rock fragment size
distributions was achieved through the analysis of drone-captured imagery,
coupled with the application of an enhanced Unet semantic segmentation model
integrated with an expansion-based post-processing technique. The quarry slope
was stratified into four vertical sections, with the size distribution of each
section quantified via ellipsoid shape approximations. Our results disclose
pronounced vertical segregation patterns, with finer particles concentrated in
the upper slope regions and coarser particles in the lower. Utilizing relative
characteristic diameters, we offered insight into the degree of segregation,
thereby illustrating the spatial heterogeneity in fragment size more clearly.
The techniques outlined in this study deliver a scalable and accurate method
for assessing fragment size distribution, with the potential to better inform
resource management and operational decisions in quarry management.

应用先进的图像分析方法，采用改进的 Unet 语义分割模型和基于扩展的后处理技术，成功地刻画了爆破岩石颗粒的细分离现象，并通过相对特征直径提供了岩石颗粒尺寸的空间异质性，为采石场管理中资源管理和运营决策提供了更好的信息。