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Engineering with Computers
Erschienen in: Engineering with Computers 2/2011

01.04.2011 | Original Article

Application of soft computing to predict blast-induced ground vibration

verfasst von: Manoj Khandelwal, D. Lalit Kumar, Mohan Yellishetty

Erschienen in: Engineering with Computers | Ausgabe 2/2011

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Abstract

In this study, an attempt has been made to evaluate and predict the blast-induced ground vibration by incorporating explosive charge per delay and distance from the blast face to the monitoring point using artificial neural network (ANN) technique. A three-layer feed-forward back-propagation neural network with 2-5-1 architecture was trained and tested using 130 experimental and monitored blast records from the surface coal mines of Singareni Collieries Company Limited, Kothagudem, Andhra Pradesh, India. Twenty new blast data sets were used for the validation and comparison of the peak particle velocity (PPV) by ANN and conventional vibration predictors. Results were compared based on coefficient of determination and mean absolute error between monitored and predicted values of PPV.
Vorheriger Artikel The implementation of a direct search approach for the resolution of complex and changing rule-based problems
Nächster Artikel A numerical study on the fatigue and rolling contact fatigue behaviour of PVD-coated steel and titanium spur gears

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Literatur
1.
Ambraseys NR, Hendron AJ (1968) Dynamic behaviour of rock masses: rock mechanics in engineering practices. Wiley, London
2.
Bureau of Indian Standard (1973) Criteria for safety and design of structures subjected to underground blast. ISI Bulletin IS-6922
3.
Cai JG, Zhao J (1997) Use of neural networks in rock tunneling. In: Proceedings of computer methods and advances in geomechanics, IACMAG, China, pp 613–618
4.
Dowding CH (1985) Blast vibration monitoring and control. Prentice-Hall Inc, Englewoods Cliffs
5.
Duvall, WI, Petkof B (1959) Spherical propagation of explosion generated strain pulses in rock. USBM RI, 5483, p 21
6.
Hagan TN (1973) Rock breakage by explosives, In: Proceedings of national symposium on rock fragmentation, Adelaide, pp 1–17
7.
ISRM (1992) Suggested method for blast vibration monitoring. Int J Rock Mech Min Sci Geomech Abstr 29:145–146CrossRef
8.
Khandelwal M, Singh TN (2005) Prediction of blast-induced air overpressure in opencast mine. Noise Vib Worldw 36:7–16CrossRef
9.
Khandelwal M, Singh TN (2006) Prediction of blast-induced ground vibrations and frequency in opencast mine—a neural network approach. J Sound Vib 289:711–725CrossRef
10.
Khandelwal M, Singh TN (2009) Prediction of blast-induced ground vibrations using artificial neural network. Int J Rock Mech Min Sci 46:1214–1222CrossRef
11.
Khandelwal M, Singh TN (2002) Prediction of waste dump stability by an intelligent approach. In: National symposium on new equipment—new technology, management and safety, ENTMS, Bhubaneshwar, pp 38–45
12.
Khandelwal M (2008) Evaluation and prediction of blast-induced ground vibration and frequency for surface mine—a neural network approach. Ph.D. Thesis, Indian Institute of Technology, Bombay, India
13.
Kosko B (1994) Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence. Prentice Hall, New Delhi
14.
Langefors U, Kihlstrom B (1963) The modern technique of rock blasting. Wiley, New York
15.
16.
Maity D, Saha A (2004) Damage assessment in structure from changes in static parameters using neural networks. Sadhana 29:315–327CrossRef
17.
Maulenkamp F, Grima MA (1999) Application of neural networks for the prediction of the unconfined compressive strength (UCS) from Equotip Hardness. Int J Rock Mech Min Sci 36:29–39CrossRef
18.
Mohamed MT (2009) Artificial neural network for prediction and control of blasting vibrations in Assiut (Egypt) limestone quarry. Int J Rock Mech Min Sci 46:426–431CrossRef
19.
Monjezi M, Dehghani H (2008) Evaluation of effect of blasting pattern parameters on back break using neural networks. Int J Rock Mech Min Sci 45(8):1446–1453CrossRef
20.
Neaupane KM, Adhikari NR (2006) Prediction of tunneling-induced ground movement with the multi-layer perceptron. Int J Tunnel Undergr Space Technol 21:151–159CrossRef
21.
Pal Roy P (1993) Putting ground vibration predictors into practice. Colliery Guard 241:63–67
22.
Simpson PK (1990) Artificial neural system—foundation, paradigm, application and implementations. Pergamon Press, New York
23.
Singh TN, Kanchan R, Saigal K, Verma AK (2004) Prediction of P-wave velocity and anisotropic properties of rock using Artificial Neural Networks technique. J Sci Ind Res 63:32–38
24.
Singh VK, Singh D, Singh TN (2001) Prediction of strength properties of some schistose rock. Int J Rock Mech Min Sci 38:269–284CrossRef
25.
Siskind DE, Stagg MS, Kopp, JW, Dowding CH (1980) Structure response and damage produced by ground vibration from surface mine blasting. USBM, RI, 8507, p. 74
26.
Tawadrous AS (2006) Evaluation of artificial neural networks as a reliable tool in blast design. Int Soc Explos Eng 1:1–12
27.
Wiss JF, Linehan PW (1978) Control of vibration and air noise from surface coal mines—III. Bureau of Mines. US Report No. OFR 103 (3)-79, p 623
28.
Yang Y, Zhang Q (1997) Analysis for the results of point load testing with artificial neural network. In: Proceedings of computer methods and advances in geomechanics, IACMAG, China, pp 607–612
Metadaten
Titel
Application of soft computing to predict blast-induced ground vibration
verfasst von
Manoj Khandelwal
D. Lalit Kumar
Mohan Yellishetty
Publikationsdatum
01.04.2011
Verlag
Springer-Verlag
Erschienen in
Engineering with Computers / Ausgabe 2/2011
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-009-0157-y

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