Skip to main content
SpringerLink
Log in

Evaluation of capability of blast-induced ground vibration predictors considering measurement distance and different error measures

  • Original Article
  • Published:
Environmental Earth Sciences Aims and scope Submit manuscript

Abstract

This study aims to investigate capability of the vibration prediction approaches, comprehensively. Field investigations were performed in a sandstone quarry. All the main conventional scaled distance equations were evaluated. A multivariate equation that contains blast design parameters was created by stepwise regression. A robust artificial neural network model was constructed. Effect of the additional parameters on success of the vibration estimation was examined. The success of the equations was evaluated considering the measurement distance. Evaluation of vibrations based on the measurement distance provided an opportunity to examine effectiveness of the equations that contains inelastic attenuation factor. Suitable error measures were investigated to examine the precision of vibration estimation. Both percentage errors and symmetric errors were found to be useful. Increase in the measurement distance was resulted in increase in prediction error. The classical scaled distance equations were found to be quite successful. The multivariate equation and artificial neural network model did not made better predictions than the scaled distance equations for long distance. The equations with inelastic attenuation formula do not have any advantage over classical scaled distance equations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Aler J, Du Mouza J, Arnould M (1996) Evaluation of blast fragmentation efficiency and its prediction by multivariate analysis procedures. Int J Rock Mech Mın 33:189–196. https://doi.org/10.1016/0148-9062(95)00055-0

    Article  Google Scholar 

  • Ambraseys NR, Hendron AJ (1968) Dynamic behaviour of rockmasses. In: Stagg KG, Zienkiewicz OC (eds) Rock mechanics in engineering practice. Wiley, London, pp 203–207

    Google Scholar 

  • Armaghani DJ, Momeni E, Abad SVANK, Khandelwal M (2015) Feasibility of ANFIS model for prediction of ground vibrations resulting from quarry blasting. Environ Earth Sci 74:2845–2860. https://doi.org/10.1007/s12665-015-4305-y

    Article  Google Scholar 

  • Armstrong JS, Collopy F (1992) Error measures for generalizing about forecasting methods: empirical comparisons. Int J Forecast 8:69–80. https://doi.org/10.1016/0169-2070(92)90008-W

    Article  Google Scholar 

  • Ash RL (1963) The mechanics of rock breakage (part 2)—standards for blast design. Pit Quarry 56:118–122

    Google Scholar 

  • Attewell PB, Farmer IW, Haslam D (1965) Prediction of ground vibration parameters from major quarry blasts. Min Miner Eng 5:621–626

    Google Scholar 

  • Beale MH, Hagan MT, Demuth HB (2018) Neural network toolbox user’s guide. The MathWorks Inc, Natick

    Google Scholar 

  • Birch WJ, Chaffer R (1983) Prediction of ground vibrations from blasting on opencast sites. Inst Min Metall Trans Sec A (Min Ind) 92:A102–A107

    Google Scholar 

  • Davies B, Farmer IW, Attewell PB (1964) Ground vibration from shallow sub-surface blasts. The Eng 217:553–559

    Google Scholar 

  • Davydenko A, Fildes R (2016) Forecast error measures: critical review and practical recommendations. In: Gilliland M, Tashman L, Sglavo U (eds) Business forecasting: practical problems and solutions. Wiley, New Jersey, pp 238–250

    Google Scholar 

  • Dehghani H, Ataee-pour M (2011) Development of a model to predict peak particle velocity in a blasting operation. Int J Rock Mech Min 48:51–58. https://doi.org/10.1016/j.ijrmms.2010.08.005

    Article  Google Scholar 

  • Dindarloo SR (2015) Prediction of blast-induced ground vibrations via genetic programming. Int J Min Sci Technol 25:1011–1015. https://doi.org/10.1016/j.ijmst.2015.09.020

    Article  Google Scholar 

  • Dowding CH (1971) Response of buildings to ground vibration resulting from construction blasting. Ph.D. thesis, Department of Civil Engineering, University of Illinois at Urbana-Champaign, Illinois, p 204

  • Duvall WI, Petkof B (1959) Spherical propagation of explosion generated strain pulses in rock, RI 5483. US Bureau of Mines, Washington DC

    Google Scholar 

  • Faradonbeh RS, Armaghani DJ, Monjezi M (2016) Development of a new model for predicting flyrock distance in quarry blasting: a genetic programming technique. B Eng Geol Environ 75:993–1006. https://doi.org/10.1007/s10064-016-0872-8

    Article  Google Scholar 

  • Garson GD (2014) Multiple regression. Statistical Associates Publishing, Asheboro

    Google Scholar 

  • Ghasemi E, Ataei M, Hashemolhosseini H (2013) Development of a fuzzy model for predicting ground vibration caused by rock blasting in surface mining. J Vib Control 19:755–770. https://doi.org/10.1177/1077546312437002

    Article  Google Scholar 

  • Ghosh A, Daemen JK (1983) A simple new blast vibration predictor based on wave propagation laws. In: Proceedings of the 24th US symposium on rock mechanics, Texas USA, pp 151–162

  • Goodwin P, Lawton R (1999) On the asymmetry of the symmetric MAPE. Int J Forecast 15:405–408. https://doi.org/10.1016/S0169-2070(99)00007-2

    Article  Google Scholar 

  • Gujarati DN (2006) Essentials of econometrics, 3rd edn. McGraw-Hill-Irwin, Boston

    Google Scholar 

  • Gupta RN, Roy PP, Bagachi A, Singh B (1987) Dynamic effects in various rock mass and their predictions. J Min Met Fuels 35:55–462

    Google Scholar 

  • Gupta RN, Roy PP, Sing B (1988) On a blast induced blast vibration predictor for efficient blasting. In: Proceedings of the 22nd international conference of safety in mines, Beijing China, pp 1015–1021

  • Gustafsson R (1973) Swedish blasting technique. SPI, Gothenburg

    Google Scholar 

  • Hajihassani M, Armaghani DJ, Monjezi M, Mohamad ET, Marto A (2016) Blast-induced air and ground vibration prediction: a particle swarm optimization-based artificial neural network approach. Envıron Earth Scı 74:2799–2817. https://doi.org/10.1007/s12665-015-4274-1

    Article  Google Scholar 

  • Hasanipanah M, Naderi R, Kashir J, Noorani SA, Qaleh AZA (2016) Prediction of blast-produced ground vibration using particle swarm optimization. Eng Comput 33:173–179. https://doi.org/10.1007/s00366-016-0462-1

    Article  Google Scholar 

  • Hudaverdi T, Akyildiz O (2017) Investigation of the site-specific character of blast vibration prediction. Environ Earth Sci 76:138. https://doi.org/10.1007/s12665-017-6456-5

    Article  Google Scholar 

  • Hudaverdi T, Kuzu C, Fisne A (2012) Investigation of the blast fragmentation using the mean fragment size and fragmentation index. Int J Rock Mech Min 56:136–145. https://doi.org/10.1016/j.ijrmms.2012.07.028

    Article  Google Scholar 

  • Hyndman RJ, Koehler AB (2006) Another look at measures of forecast accuracy. Int J Forecast 22:679–688. https://doi.org/10.1016/j.ijforecast.2006.03.001

    Article  Google Scholar 

  • Indian Standards (1973) Criteria for safety and design of structures subjected to underground blast, Bulletin no: IS-6922. Indian Standards, New Delhi

    Google Scholar 

  • ISEE (2015) Field practice guidelines for blasting seismographs. International Society of Explosives Engineers, Cleveland

    Google Scholar 

  • Jaeger JC, Cook NGW (1979) Fundamentals of rock mechanics, 3rd edn. Chapman and Hall, London

    Google Scholar 

  • Khandelwal M (2012) Application of an expert system for the assessment of blast vibration. Geotech Geol Eng 30:205–217. https://doi.org/10.1007/s10706-011-9463-4

    Article  Google Scholar 

  • Khandelwal M, Singh TN (2007) Evaluation of blast-induced ground vibration predictors. Soil Dyn Earthq Eng 27:116–125. https://doi.org/10.1016/j.soildyn.2006.06.004

    Article  Google Scholar 

  • Khandelwal M, Singh TN (2009) Prediction of blast-induced ground vibration using artificial neural network. Int J Rock Mech Min 46:1214–1222. https://doi.org/10.1016/j.ijrmms.2009.03.004

    Article  Google Scholar 

  • Kosko B (1994) Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence. Prentice Hall, New Delhi

    Google Scholar 

  • Langefors U, Kihlstrom B (1963) The modern technique of rock blasting. Wiley, New York

    Google Scholar 

  • Lippman RP (1987) Introduction to computing with neural nets. IEEE Assp Mag 4:4–22

    Article  Google Scholar 

  • McNeill FM, Thro E (1994) Fuzzy logic: a practical approach. AP Professional, Boston

    Google Scholar 

  • Mehrotra K, Mohan CK, Ranka S (2000) Elements of artificial neural networks. MIT Press, Cambridge

    Google Scholar 

  • Monjezi M, Hasanipanah M, Khandelwal M (2013) Evaluation and prediction of blast-induced ground vibration at Shur River Dam, Iran, by artificial neural network. Neural Comput Appl 22:1637–1643. https://doi.org/10.1007/s00521-012-0856-y

    Article  Google Scholar 

  • Nicholls HR, Johnson CF, Duvall WI (1971) Blasting vibrations and their effects on structures, Bulletin no. 656. US Bureau of Mines, Washington DC

    Google Scholar 

  • Richart FE Jr, Hall JR Jr, Woods RD (1970) Vibrations of soils and foundations. Prentice-Hall, New Jersey

    Google Scholar 

  • Roy PP (1991) Vibration control in an opencast mine based on improved blast vibration predictors. Min Sci Technol 12:157–165. https://doi.org/10.1016/0167-9031(91)91642-U

    Article  Google Scholar 

  • Saadat M, Khandelwal M, Monjezi M (2014) An ANN-based approach to predict blast-induced ground vibration of Gol-E-Gohar iron ore mine, Iran. J Rock Mech Geotech Eng 6:67–76. https://doi.org/10.1016/j.jrmge.2013.11.001

    Article  Google Scholar 

  • Shcherbakov MV, Brebels A, Shcherbakova NL, Tyukov AP, Janovsky TA, Kamaev VA (2013) A survey of forecast error measures. World Appl Sci J 24:171–176

    Google Scholar 

  • Shoop SA, Daemen JJK (1983) Site-specific predictions of ground vibrations induced by blasting. In: Proceedings of TMS/AIME meeting, Atlanta USA, pp 83–95

  • Singh TN (2004) Artificial neural network approach for prediction and control of ground vibrations in mines. Min Technol (Trans Inst Min Metall A) 113:251–256. https://doi.org/10.1179/037178404225006137

    Article  Google Scholar 

  • Tabachnick BG, Fidell LS (2013) Using multivariate statistics. Pearson Education, New Jersey

    Google Scholar 

  • Tripathy G, Gupta ID (2002) Prediction of ground vibrations due to construction blasts in different types of rock. Rock Mech Rock Eng 35:195–204. https://doi.org/10.1007/s00603-001-0022-9

    Article  Google Scholar 

  • Tugrul A, Undul O (2006) Engineering geological characteristics of Istanbul greywackes. In: Proceedings of the 10th international association for engineering geology and the environment (IAEG) congress, Nottingham United Kingdom, paper no. 395

  • Zadeh L, Kacprzyk J (eds) (1992) Fuzzy logic for the management of uncertainty. Wiley, New York

    Google Scholar 

  • Zhou J, Li X, Shi X (2012) Long-term prediction model of rockburst in underground openings using heuristic algorithms and support vector machines. Safety Sci 50:629–644. https://doi.org/10.1016/j.ssci.2011.08.065

    Article  Google Scholar 

  • Zhou J, Li X, Mitri HS (2016) Classification of rockburst in underground projects: comparison of ten supervised learning methods. J Comput Civil Eng 30:1–19. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000553

    Article  Google Scholar 

Download references

Acknowledgements

This study was supported by the Research Fund of the Istanbul Technical University (No: MGA-2017-40581), and partially supported by The Scientific and Technological Research Council of Turkey—TUBİTAK—(No: 217M071). The authors are grateful to the Istanbul Technical University and TUBITAK for their financial support.

Author information

Authors and Affiliations

  1. Department of Mining Engineering, Istanbul Technical University, Maslak, 34469, Istanbul, Turkey

    Turker Hudaverdi & Ozge Akyildiz

Authors
  1. Turker Hudaverdi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ozge Akyildiz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Turker Hudaverdi.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hudaverdi, T., Akyildiz, O. Evaluation of capability of blast-induced ground vibration predictors considering measurement distance and different error measures. Environ Earth Sci 78, 421 (2019). https://doi.org/10.1007/s12665-019-8427-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12665-019-8427-5

Keywords

Search

Navigation