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Establishment and Application of Blasting Vibration Prediction System based on SSA-XGBoost
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Ping ZOU1, Liang WANG2, Yong DAI1, Chun-yang ZHANG3
Blasting | 2023, 40(3) : 199 - 205
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Blasting | 2023, 40(3): 199-205
• BLASTING SAFETY •
Establishment and Application of Blasting Vibration Prediction System based on SSA-XGBoost
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Ping ZOU1, Liang WANG2, Yong DAI1, Chun-yang ZHANG3
Affiliations
  • 1.Zijin (Changsha) Engineering Technology Co., Ltd., Changsha 410000, China
  • 2.NorinMinging Co., Ltd., Beijing 100053, China
  • 3.School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, China
Published: 2023-09-01 doi: 10.3963/j.issn.1001-487X.2023.03.027
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The peak particle velocity (PPV) of blasting vibration is an important index to measure the impact of blasting vibration on surrounding environment and structures. In order to improve the reliability of PPV prediction, a model based on extreme gradient boosting optimized by the sparrow search algorithm was proposed, and a corresponding blasting vibration prediction system was built using the App Designer of MATLAB. The maximum charge per delay, distance from blast center to measuring point, and elevation difference between measuring point and blast center were selected as the input parameters of 36 sets of training data and 5 sets of test data for the model to predict PPV. The results show that the proposed SSA-XGBoost model has a smaller average relative error compared with the GA-BPNN model and BPNN model, and it has a higher prediction accuracy and better stability proved by the Taylor graph.

blasting vibration  /  peak particle velocity  /  sparrow search algorithm  /  extreme gradient boosting  /  prediction system
Ping ZOU, Liang WANG, Yong DAI, Chun-yang ZHANG. Establishment and Application of Blasting Vibration Prediction System based on SSA-XGBoost[J]. Blasting, 2023 , 40 (3) : 199 -205 . DOI: 10.3963/j.issn.1001-487X.2023.03.027
Funding
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  • National Natural Science Foundation of China(52174088)
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Year 2023 volume 40 Issue 3
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Article Info
doi: 10.3963/j.issn.1001-487X.2023.03.027
  • Receive Date：2023-04-18
  • Online Date：2026-03-20
  • Published：2023-09-01
Article Data
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History
  • Received：2023-04-18
Funding
National Natural Science Foundation of China(52174088)
Affiliations
    1.Zijin (Changsha) Engineering Technology Co., Ltd., Changsha 410000, China
    2.NorinMinging Co., Ltd., Beijing 100053, China
    3.School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, China

Corresponding:

ZHANG Chun-yang (1981-), male, Ph. D, associate professor, mainly engaged in research on mining and rock mechanics, (E-mail)
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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