Machine learning techniques to classify drill bit wear and rock strength from drilling

<p dir="ltr"><b>Numerical data used for the study</b></p><ol><li>Numerical data was generated using a lumped parameter axial-torsional model by Gupta and Wahi, 2016.</li><li>The files in the Matlab and Maple files folder contain the results o...

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Bibliographic Details
Main Author:	Jong Park (21756368) (author)
Other Authors:	Stephan Heyns (12065027) (author)
Published:	2025
Subjects:	Signal processing Dynamics, vibration and vibration control Mechanical engineering asset management Numerical modelling and mechanical characterisation Modelling and simulation Neural networks Machine learning not elsewhere classified Rock drilling vibrations Random forest Convolutional neural network Rock strength classification Drill bit wear classification SDG 7 Affordable and clean energy SDG 9 Industry, innovation and infrastructure
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Machine learning techniques to classify drill bit wear and rock strength from drilling

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