Application of coupled analysis methods for prediction of blast-induced dominant vibration frequency. Li, H., Li, X., Li, J., Xia, X., & Wang, X. Earthquake Engineering and Engineering Vibration, 15(1):153-162, 2016. doi abstract bibtex Blast-induced dominant vibration frequency (DVF) involves a complex, nonlinear and small sample system considering rock properties, blasting parameters and topography. In this study, a combination of grey relational analysis and dimensional analysis procedures for prediction of dominant vibration frequency are presented. Six factors are selected from extensive effect factor sequences based on grey relational analysis, and then a novel blast-induced dominant vibration frequency prediction is obtained by dimensional analysis. In addition, the prediction is simplified by sensitivity analysis with 195 experimental blast records. Validation is carried out for the proposed formula based on the site test database of the firstperiod blasting excavation in the Guangdong Lufeng Nuclear Power Plant (GLNPP). The results show the proposed approach has a higher fitting degree and smaller mean error when compared with traditional predictions.
@article{
title = {Application of coupled analysis methods for prediction of blast-induced dominant vibration frequency},
type = {article},
year = {2016},
keywords = {dimensional analysis,dominant vibration frequency,grey relational analysis,prediction,sensitivity analysis},
pages = {153-162},
volume = {15},
id = {bce79342-9cd1-361b-aa57-b76e4eb75725},
created = {2019-06-30T09:07:18.158Z},
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last_modified = {2021-11-14T01:17:50.103Z},
read = {false},
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authored = {true},
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citation_key = {Li2016g},
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abstract = {Blast-induced dominant vibration frequency (DVF) involves a complex, nonlinear and small sample system considering rock properties, blasting parameters and topography. In this study, a combination of grey relational analysis and dimensional analysis procedures for prediction of dominant vibration frequency are presented. Six factors are selected from extensive effect factor sequences based on grey relational analysis, and then a novel blast-induced dominant vibration frequency prediction is obtained by dimensional analysis. In addition, the prediction is simplified by sensitivity analysis with 195 experimental blast records. Validation is carried out for the proposed formula based on the site test database of the firstperiod blasting excavation in the Guangdong Lufeng Nuclear Power Plant (GLNPP). The results show the proposed approach has a higher fitting degree and smaller mean error when compared with traditional predictions.},
bibtype = {article},
author = {Li, Haibo and Li, Xiaofeng and Li, Jianchun and Xia, Xiang and Wang, Xiaowei},
doi = {10.1007/s11803-016-0312-6},
journal = {Earthquake Engineering and Engineering Vibration},
number = {1}
}
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