Validation of the accuracy of surface area and volume estimation in a grain size distribution evaluation system for thermal storage rocks using an RGB-D camera

Abstract

A simple technique for evaluating the grain size distribution of rocks is required to quickly understand the heat storage and dissipation behavior of rocks, which are inexpensive heat storage materials. We developed the grain size distribution evaluation system using an RGB-D camera. The system uses an image segmentation AI model and a shape completion algorithm to estimate the shape of individual rocks in an RGB-D image and obtain their grain size distribution. The accuracy of the estimation of surface area equivalent diameter and volume equivalent diameter distributions of rocks was verified using rocks with known shapes.