Quantification of paste homogeneity by vision-based identification method: Case study for an industrial mixer
Published in Developments in the Built Environment, 2025
This study develops a vision-based device for real-time monitoring of paste homogeneity during mixing processes. An image segmentation method is proposed to identify non-paste regions and detect areas of insufficient uniformity. To quantitatively assess mixing quality, a non-homogeneity factor is defined, providing an objective measure of paste uniformity. The relationship between blade position and paste homogeneity is further modeled using Gaussian process regression, offering insights into mixing dynamics. The effectiveness of the proposed metric is validated in a paste backfill station, where the results demonstrate strong consistency with engineers’ practical assessments.
Recommended citation: Xiaorui Li, Zhaolin Yuan, Hezheng Wang, Yong Wang, Xiaojuan Ban, "Quantification of paste homogeneity by vision-based identification method: Case study for an industrial mixer." Developments in the Built Environment, 2025.
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