Statistical analysis of blast-induced vibration near an open pit mine
Abstract Blast-induced vibration may be harmful to facilities in the vicinity of operating mines, mainly causing structural damage and human discomfort. This study presents an application of multivariate statistics to predict vibration levels regarding their potential to cause structural damage and...
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| Format: | Article |
| Language: | English |
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Academia Brasileira de Ciências
2023-08-01
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| Series: | Anais da Academia Brasileira de Ciências |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652023000201705&tlng=en |
| _version_ | 1797681793030160384 |
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| author | PAULO FILIPE T. LOPES JOSÉ AURÉLIO M. DA LUZ TIAGO M. PEREIRA LEANDRO GERALDO C. SILVEIRA |
| author_facet | PAULO FILIPE T. LOPES JOSÉ AURÉLIO M. DA LUZ TIAGO M. PEREIRA LEANDRO GERALDO C. SILVEIRA |
| author_sort | PAULO FILIPE T. LOPES |
| collection | DOAJ |
| description | Abstract Blast-induced vibration may be harmful to facilities in the vicinity of operating mines, mainly causing structural damage and human discomfort. This study presents an application of multivariate statistics to predict vibration levels regarding their potential to cause structural damage and human discomfort. An extensive seismic monitoring campaign was executed in a large open-pit iron ore mine, near a small village, to gather a dataset for a predictive multivariate analysis. Ten blasting events have produced a dataset of 158 valid measurements. Three classes of vibration peak velocity were adopted from legal standards, which later supported a cluster analysis. Then, it was possible to compare how much these two classification modalities respond to discriminant analysis. The next step was to carry out a principal component analysis (PCA) from the original database, and, comparatively, to plot both the scores concerning the classes derived from the vibration standard and those from the groups obtained from cluster analysis. PCA has considerably explained the data variability, while the three classes from cluster analysis resulted very similar to the corresponding ones from the vibration standards. The results have demonstrated that multivariate statistics may be applied to manage blasting-induced vibration and its deleterious effects with few adjustments and automation. |
| first_indexed | 2024-03-11T23:50:09Z |
| format | Article |
| id | doaj.art-6313dc8a37a34627840ff7aff21db8fa |
| institution | Directory Open Access Journal |
| issn | 1678-2690 |
| language | English |
| last_indexed | 2024-03-11T23:50:09Z |
| publishDate | 2023-08-01 |
| publisher | Academia Brasileira de Ciências |
| record_format | Article |
| series | Anais da Academia Brasileira de Ciências |
| spelling | doaj.art-6313dc8a37a34627840ff7aff21db8fa2023-09-19T07:41:36ZengAcademia Brasileira de CiênciasAnais da Academia Brasileira de Ciências1678-26902023-08-0195suppl 110.1590/0001-3765202320210008Statistical analysis of blast-induced vibration near an open pit minePAULO FILIPE T. LOPEShttps://orcid.org/0000-0001-7320-3093JOSÉ AURÉLIO M. DA LUZhttps://orcid.org/0000-0002-7952-2439TIAGO M. PEREIRAhttps://orcid.org/0000-0003-2564-5895LEANDRO GERALDO C. SILVEIRAhttps://orcid.org/0000-0002-8848-8789Abstract Blast-induced vibration may be harmful to facilities in the vicinity of operating mines, mainly causing structural damage and human discomfort. This study presents an application of multivariate statistics to predict vibration levels regarding their potential to cause structural damage and human discomfort. An extensive seismic monitoring campaign was executed in a large open-pit iron ore mine, near a small village, to gather a dataset for a predictive multivariate analysis. Ten blasting events have produced a dataset of 158 valid measurements. Three classes of vibration peak velocity were adopted from legal standards, which later supported a cluster analysis. Then, it was possible to compare how much these two classification modalities respond to discriminant analysis. The next step was to carry out a principal component analysis (PCA) from the original database, and, comparatively, to plot both the scores concerning the classes derived from the vibration standard and those from the groups obtained from cluster analysis. PCA has considerably explained the data variability, while the three classes from cluster analysis resulted very similar to the corresponding ones from the vibration standards. The results have demonstrated that multivariate statistics may be applied to manage blasting-induced vibration and its deleterious effects with few adjustments and automation.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652023000201705&tlng=enrock blastingvibrationmultivariate analysiscluster analysisdiscriminant analysisprincipal component analysis |
| spellingShingle | PAULO FILIPE T. LOPES JOSÉ AURÉLIO M. DA LUZ TIAGO M. PEREIRA LEANDRO GERALDO C. SILVEIRA Statistical analysis of blast-induced vibration near an open pit mine Anais da Academia Brasileira de Ciências rock blasting vibration multivariate analysis cluster analysis discriminant analysis principal component analysis |
| title | Statistical analysis of blast-induced vibration near an open pit mine |
| title_full | Statistical analysis of blast-induced vibration near an open pit mine |
| title_fullStr | Statistical analysis of blast-induced vibration near an open pit mine |
| title_full_unstemmed | Statistical analysis of blast-induced vibration near an open pit mine |
| title_short | Statistical analysis of blast-induced vibration near an open pit mine |
| title_sort | statistical analysis of blast induced vibration near an open pit mine |
| topic | rock blasting vibration multivariate analysis cluster analysis discriminant analysis principal component analysis |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652023000201705&tlng=en |
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