Advanced Muck Pile Characterization for Optimized Blast Design and Excavator Loading Efficiency: A Synergistic Approach Using UAVs, PCA, and AI
Journal Title: GeoStruct Innovations - Year 2024, Vol 2, Issue 4
Abstract
Muck pile characteristics play a pivotal role in optimizing mining operations, particularly in understanding the post-blast behavior of throw, drop, and lateral spread, which directly impacts the selection and performance of loaders. The parameters of blast design are crucial in determining muck pile formation, influencing both loader efficiency and overall operational productivity. This study explores the effects of various blast design parameters on key muck pile attributes through a series of controlled blast experiments. Principal component analysis (PCA) was employed to identify the blast design factors most influential on muck pile characteristics, enabling the formulation of precise blast designs. The experiments were conducted across four phases at the OCI RGIII mines of Singareni Collieries Company Limited (SCCL), using advanced blast planning software to ensure accurate parameter implementation based on PCA results. Muck pile characteristics were assessed with the assistance of sophisticated artificial intelligence (AI) tools, providing valuable insights into blast optimization. The results revealed that blast designs incorporating a 1.35 spacing-to-burden (S/B) ratio, 0.9(B) stemming, 1-meter decking, and a V firing initiation pattern significantly enhanced muck pile performance. Specifically, these configurations reduced drop height by 3 meters, decreased throw distance by 5.9 meters, and increased lateral spread by 19.3 meters. These optimized muck pile attributes facilitated smoother loader operation, ultimately improving loading efficiency and the overall productivity of mining processes.
Authors and Affiliations
Nidumukkala Sri Chandrahas, Yewuhalashet Fissha, Nageswara Rao Cheepurupalli
Keywords
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- EP ID EP756127
- DOI https://doi.org/10.56578/gsi020402
- Views 30
- Downloads 0
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