Parameter Optimization and Fragmentation Prediction of Fan-Shaped Deep Hole Blasting in Sanxin Gold and Copper Mine

For San-Xin gold and copper mine, deep blasting large block rate is high resulting in difficulty transporting the ore out; secondary not only increases costs but more likely to cause top bottom plate of underground become loose causing safety hazards. Based on research background Sanxin hole parameters were determined by single-hole, variable-hole pitch, oblique tests, further using inversion method determine optimal parameters. Meanwhile, PSO-BP neural network was used predict blasting. The results study showed that minimum resistance line 1.24–1.44 m, which lower than 1.6–1.8 m original design, one reasons for higher rate. In addition, fragmentation prediction model predicts optimized predicted a 6.83% after optimization Its accuracy high, parameter can effectively reduce It reasonably pieces produced blasting, improve efficiency, save enterprises. result has wide applicability provide solutions mines also have problems with