Development of a fuzzy model for predicting ground vibration caused by rock blasting in surface mining

Ground vibration is an integral part of the rock blasting process in surface mines, which may cause severe damages to structures and plants in the nearby environment. Therefore, its prediction plays an important role in the minimization of environmental impacts. The peak particle velocity (PPV) is an important predictor for ground vibration. In this paper, first a fuzzy logic model was developed to predict PPV based on collected data from blasting events in Sarcheshmeh copper mine, located in the southwest of Iran. The predictive fuzzy model was implemented on the fuzzy logic toolbox of MATLAB using the Mamdani algorithm. Then, the PPV was predicted by conventional empirical predictors used in blasting practice and also by multiple regression analysis. Finally, a comparative analysis between the results obtained by the fuzzy model and common vibration predictors was carried out. The results indicated the high predictive capacity of fuzzy model, which can be used as a reliable predictor of ground vibration for the studied mine.

[1]  P B Attewell,et al.  GROUND VIBRATION FROM SHALLOW SUB-SURFACE BLASTS , 1964 .

[2]  Jafar Khademi Hamidi,et al.  Application of Fuzzy Set Theory to Rock Engineering Classification Systems: An Illustration of the Rock Mass Excavability Index , 2010 .

[3]  Candan Gokceoglu,et al.  A fuzzy model to predict the uniaxial compressive strength and the modulus of elasticity of a problematic rock , 2004, Eng. Appl. Artif. Intell..

[4]  P. Pal Roy,et al.  Vibration control in an opencast mine based on improved blast vibration predictors , 1991 .

[5]  Amitava Ghosh,et al.  A SIMPLE NEW BLAST VIBRATION PREDICTOR(BASED ON WAVE PROPAGATION LAWS) , 1983 .

[6]  T. N. Singh,et al.  Sensitivity of total charge and maximum charge per delay on ground vibration , 2010 .

[7]  M. Alvarez Grima,et al.  Modeling tunnel boring machine performance by neuro-fuzzy methods , 2000 .

[8]  Ercan Arpaz,et al.  Studies on the effect of burden width on blast-induced vibration in open-pit mines , 2007 .

[9]  T. N. Singh,et al.  Intelligent systems for ground vibration measurement: a comparative study , 2011, Engineering with Computers.

[10]  Oguz Kaynar,et al.  Multiple regression, ANN (RBF, MLP) and ANFIS models for prediction of swell potential of clayey soils , 2010, Expert Syst. Appl..

[11]  A. Kahriman Analysis of ground vibrations caused by bench blasting at Can Open-pit Lignite Mine in Turkey , 2002 .

[12]  Adnan Aydin,et al.  Fuzzy set approaches to classification of rock masses , 2004 .

[13]  Božo Soldo,et al.  Estimation of particle velocity based on blast event measurements at different rock units , 2010 .

[14]  M. T. Mohamed,et al.  Performance of fuzzy logic and artificial neural network in prediction of ground and air vibrations , 2011 .

[15]  C. Kuzu,et al.  The importance of site-specific characters in prediction models for blast-induced ground vibrations , 2008 .

[16]  T. Singh,et al.  Evaluation of blast-induced ground vibration predictors , 2007 .

[17]  M. P. Roy,et al.  Evolution of effective charge weight per delay for prediction of ground vibrations generated from blasting in a limestone mine , 2006 .

[18]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[19]  M. Iphar,et al.  Prediction of ground vibrations resulting from the blasting operations in an open-pit mine by adaptive neuro-fuzzy inference system , 2008 .

[20]  Sushil Bhandari,et al.  Engineering rock blasting operations , 1997 .

[21]  Adnan Konuk,et al.  Evaluation of ground vibration effect of blasting operations in a magnesite mine , 2009 .

[22]  Candan Gokceoglu,et al.  A fuzzy triangular chart to predict the uniaxial compressive strength of the Ankara agglomerates from their petrographic composition , 2002 .

[23]  Robert Babuška,et al.  Fuzzy model for the prediction of unconfined compressive strength of rock samples , 1999 .

[24]  H. Ergin,et al.  An assessment of environmental impacts of quarry-blasting operation: a case study in Istanbul, Turkey , 2005 .

[25]  Marilena Cardu,et al.  An Assessment of Blasting Vibrations: A Case Study on Quarry Operation , 2009 .

[26]  C. Valdivia,et al.  Vibration Simulation Method to Control Stability in the Northeast Corner of Escondida Mine , 2003 .

[27]  D. P. Blair,et al.  Surface vibrations due to a vertical column of explosive , 1995 .

[28]  M. T. Mohamed,et al.  Artificial neural network for prediction and control of blasting vibrations in Assiut (Egypt) limestone quarry , 2009 .

[29]  T. N. Singh,et al.  Prediction of blast-induced ground vibration using artificial neural network , 2009 .

[30]  T. N. Singh,et al.  An intelligent approach to prediction and control ground vibration in mines , 2005 .

[31]  Hesam Dehghani,et al.  Development of a model to predict peak particle velocity in a blasting operation , 2011 .

[32]  T. Singh,et al.  Prediction of blast induced ground vibrations and frequency in opencast mine: A neural network approach , 2006 .

[33]  Ali Kahriman,et al.  The analysis of ground vibrations induced by bench blasting at Akyol quarry and practical blasting charts , 2008 .

[34]  O. Acaroglu,et al.  Prediction of thrust and torque requirements of TBMs with fuzzy logic models , 2011 .

[35]  M. R. Mozdianfard,et al.  Predicting of blasting vibrations in Sarcheshmeh copper mine by neural network , 2010 .

[36]  Abdullah Fişne,et al.  Prediction of environmental impacts of quarry blasting operation using fuzzy logic , 2011, Environmental monitoring and assessment.

[37]  Ali Kahriman,et al.  Analysis of parameters of ground vibration produced from bench blasting at a limestone quarry , 2004 .

[38]  Masoud Monjezi,et al.  Predicting blast-induced ground vibration using various types of neural networks , 2010 .

[39]  U. Langefors,et al.  The modern technique of rock blasting. , 1968 .

[40]  A. I. Sofianos,et al.  Extending the Q system's prediction of support in tunnels employing fuzzy logic and extra parameters , 2006 .

[41]  M. Iphar,et al.  An application of fuzzy sets to the Diggability Index Rating Method for surface mine equipment selection , 2006 .

[42]  T. Singh,et al.  A new predictor for ground vibration prediction and its comparison with other predictors , 2004 .

[43]  Manoj Khandelwal,et al.  Application of soft computing to predict blast-induced ground vibration , 2011, Engineering with Computers.

[44]  Mohamad Ataei,et al.  Prediction of blast induced vibrations in the structures of Karoun III power plant and dam , 2011 .

[45]  T. Ross Fuzzy Logic with Engineering Applications , 1994 .