Faculty Publications
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Item Estimating rock properties using sound levels produced during drilling(Elsevier BV, 2009) Vardhan, H.; Adhikari, G.R.; Govinda Raj, M.An attempt has been made in this paper to experimentally investigate the estimation of rock properties like compressive strength and abrasivity using sound levels produced during drilling. The investigation was carried out on a laboratory scale using small portable pneumatic drilling equipment used in hard rock drilling. For this purpose, a pneumatic drill setup was fabricated for drilling vertical holes. The compressive strength and the abrasivity of various rock samples collected from the field were determined in the laboratory. A set of test conditions were defined for measurement of sound level of the pneumatic drill. Also, with the help of the experimental setup, vertical drilling was carried out on the rock samples for varying thrust and air pressure values and the corresponding A-weighted equivalent continuous sound levels were measured. Results of this study indicate that sound level can be a promising tool in estimating rock properties during drilling. © 2008 Elsevier Ltd. All rights reserved.Item ANN Models for Prediction of Sound and Penetration Rate in Percussive Drilling(Springer India sanjiv.goswami@springer.co.in, 2015) Kivade, S.B.; Murthy, C.S.N.; Vardhan, H.In the recent years, new techniques such as; Artificial Neural Network (ANN) were employed for developing of the predictive models to estimate the needed parameters. Soft computing techniques are now being used as alternate statistical tool. In this study, ANN models were developed to predict rock properties of sedimentary rock, by using penetration and sound level produced during percussive drilling. The data generated in the laboratory investigation was utilized for the development of ANN models for predicting rock properties like, uniaxial compressive strength, abrasivity, tensile strength, and Schmidt rebound number using air pressure, thrust, bit diameter, penetration rate and sound level. Further, ANN models were also developed for predicting penetration rate and sound level using air pressure, thrust, bit diameter and rock properties as input parameters. The constructed models were checked using various prediction performance indices. ANN models were more acceptable for predicting rock properties. © 2015, The Institution of Engineers (India).