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 in transporting the ore out; secondary blasting not only increases blasting costs but is more likely to cause the top and bottom plate of the underground to become loose causing safety hazards. Based on...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Minerals |
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| Online Access: | https://www.mdpi.com/2075-163X/12/7/788 |
| _version_ | 1797433277413326848 |
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| author | Bo Ke Ruohan Pan Jian Zhang Wei Wang Yong Hu Gao Lei Xiuwen Chi Gaofeng Ren Yuhao You |
| author_facet | Bo Ke Ruohan Pan Jian Zhang Wei Wang Yong Hu Gao Lei Xiuwen Chi Gaofeng Ren Yuhao You |
| author_sort | Bo Ke |
| collection | DOAJ |
| description | For San-Xin gold and copper mine, deep blasting large block rate is high resulting in difficulty in transporting the ore out; secondary blasting not only increases blasting costs but is more likely to cause the top and bottom plate of the underground to become loose causing safety hazards. Based on the research background of Sanxin gold and copper mine, deep hole blasting parameters were determined by single-hole, variable-hole pitch, and oblique hole blasting tests, further using the inversion method to determine the optimal deep hole blasting parameters. Meanwhile, the PSO-BP neural network method was used to predict the block rate in deep hole blasting. The results of the study showed that the optimal minimum resistance line was 1.24–1.44 m, which was lower than 1.6–1.8 m in the original blasting design, which was one of the reasons for the higher blasting block rate. In addition, the PSO-BP deep hole blasting fragmentation prediction model predicts the block rate of the optimized blasting parameters and predicted a block rate of 6.83% after the optimization of hole network parameters. Its prediction accuracy is high, and the blasting parameter optimization can effectively reduce the block rate. It can reasonably reduce the rate of large pieces produced by blasting, improve blasting efficiency, and save blasting costs for enterprises. The result has wide applicability and can provide solutions for underground mines that also have problems with blasting large block rate. |
| first_indexed | 2024-03-09T10:14:44Z |
| format | Article |
| id | doaj.art-c68b045a1a0940d59f96806026b2f325 |
| institution | Directory Open Access Journal |
| issn | 2075-163X |
| language | English |
| last_indexed | 2024-03-09T10:14:44Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Minerals |
| spelling | doaj.art-c68b045a1a0940d59f96806026b2f3252023-12-01T22:28:53ZengMDPI AGMinerals2075-163X2022-06-0112778810.3390/min12070788Parameter Optimization and Fragmentation Prediction of Fan-Shaped Deep Hole Blasting in Sanxin Gold and Copper MineBo Ke0Ruohan Pan1Jian Zhang2Wei Wang3Yong Hu4Gao Lei5Xiuwen Chi6Gaofeng Ren7Yuhao You8School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, ChinaSchool of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, ChinaSchool of Urban Construction, Wuchang University of Technology, Wuhan 430223, ChinaSchool of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, ChinaHubei Sanxin Gold Copper Limited Company, Huangshi 435199, ChinaHubei Sanxin Gold Copper Limited Company, Huangshi 435199, ChinaSchool of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, ChinaSchool of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, ChinaSchool of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, ChinaFor San-Xin gold and copper mine, deep blasting large block rate is high resulting in difficulty in transporting the ore out; secondary blasting not only increases blasting costs but is more likely to cause the top and bottom plate of the underground to become loose causing safety hazards. Based on the research background of Sanxin gold and copper mine, deep hole blasting parameters were determined by single-hole, variable-hole pitch, and oblique hole blasting tests, further using the inversion method to determine the optimal deep hole blasting parameters. Meanwhile, the PSO-BP neural network method was used to predict the block rate in deep hole blasting. The results of the study showed that the optimal minimum resistance line was 1.24–1.44 m, which was lower than 1.6–1.8 m in the original blasting design, which was one of the reasons for the higher blasting block rate. In addition, the PSO-BP deep hole blasting fragmentation prediction model predicts the block rate of the optimized blasting parameters and predicted a block rate of 6.83% after the optimization of hole network parameters. Its prediction accuracy is high, and the blasting parameter optimization can effectively reduce the block rate. It can reasonably reduce the rate of large pieces produced by blasting, improve blasting efficiency, and save blasting costs for enterprises. The result has wide applicability and can provide solutions for underground mines that also have problems with blasting large block rate.https://www.mdpi.com/2075-163X/12/7/788deep hole blasting parametersblasting funnelblasting fragmentationneural network |
| spellingShingle | Bo Ke Ruohan Pan Jian Zhang Wei Wang Yong Hu Gao Lei Xiuwen Chi Gaofeng Ren Yuhao You Parameter Optimization and Fragmentation Prediction of Fan-Shaped Deep Hole Blasting in Sanxin Gold and Copper Mine Minerals deep hole blasting parameters blasting funnel blasting fragmentation neural network |
| title | Parameter Optimization and Fragmentation Prediction of Fan-Shaped Deep Hole Blasting in Sanxin Gold and Copper Mine |
| title_full | Parameter Optimization and Fragmentation Prediction of Fan-Shaped Deep Hole Blasting in Sanxin Gold and Copper Mine |
| title_fullStr | Parameter Optimization and Fragmentation Prediction of Fan-Shaped Deep Hole Blasting in Sanxin Gold and Copper Mine |
| title_full_unstemmed | Parameter Optimization and Fragmentation Prediction of Fan-Shaped Deep Hole Blasting in Sanxin Gold and Copper Mine |
| title_short | Parameter Optimization and Fragmentation Prediction of Fan-Shaped Deep Hole Blasting in Sanxin Gold and Copper Mine |
| title_sort | parameter optimization and fragmentation prediction of fan shaped deep hole blasting in sanxin gold and copper mine |
| topic | deep hole blasting parameters blasting funnel blasting fragmentation neural network |
| url | https://www.mdpi.com/2075-163X/12/7/788 |
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