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Multivariate statistical analysis approach for prediction of blast-induced ground vibration

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Abstract

Excavation of coal, overburden, and mineral deposits by blasting is dominant over the globe to date, although there are certain undesirable effects of blasting which need to be controlled. Blast-induced vibration is one of the major concerns for blast designers as it may lead to structural damage. The empirical method for prediction of blast-induced vibration has been adopted by many researchers in the form of predictor equations. Predictor equations are site specific and indirectly related to physicomechanical and geological properties of rock mass as blast-induced ground vibration is a function of various controllable and uncontrollable parameters. Rock parameters for blasting face and propagation media for blast vibration waves are uncontrollable parameters, whereas blast design parameters like hole diameter, hole depth, column length of explosive charge, total number of blast holes, burden, spacing, explosive charge per delay, total explosive charge in a blasting round, and initiation system are controllable parameters. Optimization of blast design parameters is based on site condition and availability of equipment. Most of the smaller mines have predesigned blasting parameters except explosive charge per delay, total explosive charge, and distance of blast face from surface structures. However, larger opencast mines have variations in blast design parameters for different benches based on strata condition: Multivariate predictor equation is necessary in such case. This paper deals with a case study to establish multivariate predictor equation for Moher and Moher Amlohri Extension opencast mine of India. The multivariate statistical regression approach to establish linear and logarithmic scale relation between variables to predict peak particle velocity (PPV) has been used for this purpose. Blast design has been proposed based on established multivariate regression equation to optimize blast design parameters keeping PPV within legislative limits.

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Acknowledgements

The authors express their thanks and gratitude to Mine Management of Moher and Moher Amlohri Opencast Project, and M/s Sasan Power Limited for providing necessary facilities during field investigations. The input of the departmental colleagues of Rock Excavation Engineering Division, CSIR-CIMFR, Dhanbad, is thankfully acknowledged.

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Authors and Affiliations

  1. CSIR - Central Institute of Mining & Fuel Research, Dhanbad, 826 015, India

    Vivek K. Himanshu, M. P. Roy, Ranjit Kumar Paswan & P. K. Singh

  2. Indian Institute of Technology, Indian School of Mines, Dhanbad, 826004, India

    A. K. Mishra

  3. National Institute of Technology Rourkela, -76098, Rourkela, India

    Deepak Panda

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  1. Vivek K. Himanshu
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  2. M. P. Roy
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  3. A. K. Mishra
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  4. Ranjit Kumar Paswan
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  5. Deepak Panda
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  6. P. K. Singh
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Correspondence to Vivek K. Himanshu.

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Himanshu, V.K., Roy, M.P., Mishra, A.K. et al. Multivariate statistical analysis approach for prediction of blast-induced ground vibration. Arab J Geosci 11, 460 (2018). https://doi.org/10.1007/s12517-018-3796-8

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