Please use this identifier to cite or link to this item: https://idr.nitk.ac.in/jspui/handle/123456789/16455
Title: Multiple regression model for prediction of rock properties using acoustic frequency during core drilling operations
Authors: Kumar V.
Vardhan H.
Murthy C.S.N.
Issue Date: 2020
Citation: Geomechanics and Geoengineering Vol. 15 , 4 , p. 297 - 312
Abstract: The primary purpose of this study is the quantification of rock properties uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), density and abrasivity, using sound signal dominant frequencies produced during diamond core drilling operations. Rock drilling operations were performed on seven different types of rock samples, using a computer numerical control (CNC) drilling machine. Using the multiple regression analysis, satisfactory mathematical equations were developed for various physico-mechanical rock properties, as well as dominant frequencies of the sound level were generated during diamond core drilling operations. The developed prediction models demonstrated a good regression coefficient between the rock properties and dominant frequencies i.e. the R2 values are 82.50%, 78.41%, 79.40%, and 93.24% for UCS, BTS, density and abrasivity, respectively. The performances indices are: (i) root-mean-square error (RMSE) are 0.102754, 1.241652, 0.396727, and 0.697889 for UCS, BTS, density and abrasivity, respectively; (ii) values account for (VAF) is 82.50008%, 78.41137%, 79.40137%, and 93.23596% for UCS, BTS, density and abrasivity, respectively. Presently, it is in the early stages of development towards the prediction of rock properties using dominant frequencies with the help of audio signal processing in the rock drilling operation. The developed prediction models can be utilised at the early stages of mining and civil engineering projects, for the quantification of rock properties using sound signal dominant frequencies. © 2019 Informa UK Limited, trading as Taylor & Francis Group.
URI: https://doi.org/10.1080/17486025.2019.1641631
http://idr.nitk.ac.in/jspui/handle/123456789/16455
Appears in Collections:1. Journal Articles

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