Journal Articles

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/19884

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Author: search.filters.author.Vardhan, H.Subject: search.filters.subject.multiple regression

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    Sound level produced during rock drilling vis-à-vis rock properties
    (2011) Rajesh Kumar, B.; Vardhan, H.; Govindaraj, M.
    The process of drilling, in general, always produces sound. Though sound is used as a diagnostic tool in mechanical industry, its application in predicting rock property is not much explored. In this study, an attempt has been made to estimate rock properties such as uniaxial compressive strength, Schmidt rebound number and Young's modulus using sound level produced during rotary drilling. For this purpose, a computer numerical controlled vertical milling centre was used for drilling holes with drill bit diameters ranging from 6 to 20. mm with a shank length of 40. mm. Fourteen different rock types were tested. The study was carried out to develop the empirical relations using multiple regression analysis between sound level produced during drilling and rock properties considering the effects of drill bit diameter, drill bit speed and drill bit penetration rate. The F-test was used to check the validity of the developed models. The measured rock property values and the values calculated from the developed regression model are fairly close, indicating that the developed models could be efficiently used with acceptable accuracy in prediction of rock properties. © 2011 Elsevier B.V.
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    A critical review on estimation of rock properties using sound levels produced during rotary drilling
    (CAFET INNOVA Technical Society cafetinnova@gmail.com 1-2-18/103, Mohini Mansion, Gagan Mahal Road, Domalguda, Hyderabad 500029, 2012) Masood; Vardhan, H.; Mangalpady, M.; Rajesh Kumar, B.
    This paper summarizes the critical review on estimation of rock properties using sound levels produced during rotary drilling. In this paper an overall emphasis has been made to summarize the importance of sound level produced during drilling by considering various parameters like drill bit speed, penetration rate, drill bit diameter, type of drill bit and equivalent sound level produced during drilling for the estimation of rock properties. Further an attempt has also made to include the application of ANN modeling and acoustic emission in estimating rock properties. © 2012 CAFET-INNOVA TECHNICAL SOCIETY.
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    Regression analysis and ANN models to predict rock properties from sound levels produced during drilling
    (Elsevier Ltd, 2013) Rajesh Kumar, B.; Vardhan, H.; Govindaraj, M.; Vijay, G.S.
    This study aims to predict rock properties using soft computing techniques such as multiple regression, artificial neural network (MLP and RBF) models, taking drill bit speed, penetration rate, drill bit diameter and equivalent sound level produced during drilling as the input parameters. A database of 448 cases were tested for determination of uniaxial compressive strength (UCS), Schmidt rebound number (SRN), dry density (?), P-wave velocity (Vp), tensile strength (TS), modulus of elasticity (E) and percentage porosity (n) and the prediction capabilities of the models were then analyzed. Results from the analysis demonstrate that neural network approach is efficient when compared to statistical analysis in predicting rock properties from the sound level produced during drilling. © 2012 Elsevier Ltd.
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    Multiple regression model for prediction of rock properties using acoustic frequency during core drilling operations
    (Taylor and Francis Ltd., 2020) Vijaya Kumar, V.; Vardhan, H.; Murthy, C.S.N.
    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.