[1] Rivero, A.d., L.L. de Lacalle, and M.L. Penalva, Tool wear detection in dry high-speed milling based upon the analysis of machine internal signals. Mechatronics, 2008. 18(10): p. 627-633.
[2] Krúpa, V., et al., Measurement, modeling and prediction of penetration depth in rotary drilling of rocks. Measurement, 2018. 117: p. 165-175.
[3] Liptai, R., D. Harris, and C. Tatro, An introduction to acoustic emission, in Acoustic Emission. 1972, ASTM International.
[4] Adebayo, B. and J. Akande, Analysis of button bit wear and performance of down-the-hole hammer drill. Ghana Mining Journal, 2015. 15(2): p. 36-41.
[5] Phillips, C.L., J.M. Parr, and E.A. Riskin, Signals, systems, and transforms. 2003: Prentice Hall Upper Saddle River.
[6] Zborovjan, M., Identification of Minerals from Sound During Drilling. Semestral Project. TU-Kosice, 2002. 6.
[7] Zborovjan, M., I. Lesso, and L. Dorcak, Acoustic identification of rocks during drilling process. Journal of Acta Montanistica Slovaca, 2003. 8(4): p. 91-93.
[8] Lak, M., Fatehi Marji, M., Yarahmadi Bafghi, A. , Abdollahipour, A. and pourghasemi sagand, M. , Analytical solution of the explosion-induced wave propagation in rock using elastodynamic theory. Analytical and Numerical Methods in Mining Engineering, 2023. 13(34): p. 57-65.
[9] Dini, A., Ahmadi, M. and Gastasbi, K. Investigating changes in thermal and mechanical stresses of rock caused by laser drilling in high finite pressure with finite element method. Analytical and numerical methods in mining engineering, 2016. 6(12): p. 47-55.
[10] Sheng, M., et al., Frequency analysis of multi-sources acoustic emission from high-velocity waterjet rock drilling and its indicator to drilling efficiency. International Journal of Rock Mechanics and Mining Sciences, 2019. 115: p. 137-144.
[11] Mohseni, M., Atai, M. and Khalo Kakai, R. Effects of blast vibration on unplanned dilution in an underground metal mine. Analytical and numerical methods in mining engineering, 2019. 8(17): p. 77-90.
[12] Khoshouei, M. and R. Bagherpour, Application of Acoustic Emission (AE) in mining and earth sciences: a review. RGN zbornik, 2019. 47.
[13] Mokhtarian, M., Eftekhari, M. and Baghbanan, A. The application of principal component analysis in predicting the penetration coefficient of TBM using artificial neural networks. Analytical and numerical methods in mining engineering, 2013. 3(6): p. 33-43.
[14] Obert, L. and W. Duvall, Use of subaudible noises for prediction of rockbursts II—report of investigation. S Bureau of Mines, Denve, 1941.
[15] McNally, G., The prediction of geotechnical rock properties from sonic and neutron logs. Exploration Geophysics, 1990. 21(2): p. 65-71.
[16] Ward, B., German Creek Mines Rock strength from velocity logs. Unpublished report for Capricorn Coal Management Pty Ltd, 1998.
[17] Kawasaki, S., et al., An attempt to estimate mechanical properties of rocks using the Equotip hardness tester. Journal of the Japan Society of Engineering Geology, 2002. 43(4): p. 244-248.
[18] Hatherly, P., Rock strength assessment from geophysical logging. 2002.
[19] Kumar, B.R., H. Vardhan, and M. Govindaraj, Estimating rock properties using sound level during drilling: field investigation. International Journal of Mining and Mineral Engineering, 2010. 2(3): p. 169-184.
[20] Kumar, B.R., H. Vardhan, and M. Govindaraj, Sound level produced during rock drilling vis-à-vis rock properties. Engineering geology, 2011. 123(4): p. 333-337.
[21] Kumar, B.R., H. Vardhan, and M. Govindaraj, Prediction of uniaxial compressive strength, tensile strength and porosity of sedimentary rocks using sound level produced during rotary drilling. Rock mechanics& rock engineering, 2011. 44(5): p. 613-620.
[22] Gradl, C., A.W. Eustes, and G. Thonhauser, An analysis of noise characteristics of drill bits. Journal of energy resources technology, 2012. 134(1): p. 013103.
[23] Hasheminasab Zavare, F., Bagherpour, R. Baghbanan, A. and Monjezi, M. First-Order-Second-Moment Analysis of Reliability in Predicting the Rate of Penetration. Analytical and Numerical Methods in Mining Engineering, 2018. 7(14): p. 13-21.
[24] Byerlee, J., A review of rock mechanics studies in the United States pertinent to earthquake prediction, in Rock Friction and Earthquake Prediction. 1978, Springer. p. 586-602.
[25] Hardy, H.R., Application of acoustic emission techniques to rock mechanics research, in Acoustic Emission. 1972, ASTM International.
[26] Marceau, J. and Y. Moji, Application of fracture mechanics testing to process control for adhesive bonding. Document D6–41145, Boeing Commercial Airplane Company, 1973.
[27] Futó, J. and Ľ. IVANIČOVÁ. L.: Optimization of rock disintegration using the acoustic signal. in Proceedings of International Carpathian Control Conference 2003. 2003. Citeseer.
[28] Tripathi, R., et al., Monitoring of acoustic emission during the disintegration of rock. Procedia Engineering, 2016. 149: p. 481-488.
[29] Khoshouei, M., R. Bagherpour, and M.H. Jalalian, Rock Type Identification Using Analysis of the Acoustic Signal Frequency Contents Propagated While Drilling Operation. Geotechnical and Geological Engineering, 2021: p. 1-14.
[30] Knill, J., J. Franklin, and A. Malone. A study of acoustic emission from stressed rock. in International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts. 1968. Elsevier.
[31] Schön, J.H., Physical properties of rocks: Fundamentals and principles of petrophysics. Vol. 65. 2015: Elsevier.
[32] Jung, S., K. Prisbrey, and G. Wu, Prediction of rock hardness and drillability using acoustic emission signatures during indentation. International Journalof rock mechanics, 1994. 31.
[33] Miklusova, V., et al., Acoustic signal–new feature in monitoring of rock disintegration process. Contributions to geophysics geodesy, 2006. 36: p. 125-133.
[34] Leššo, I., et al., New principles of process control in geotechnics by acoustic methods. Metalurgija, 2007. 46(3): p. 165-168.
[35] Marinescu, I. and D. Axinte, A time–frequency acoustic emission-based monitoring technique to identify workpiece surface malfunctions in milling with multiple teeth cutting simultaneously. International Journal of Machine Tools Manufacture, 2009. 49(1): p. 53-65.
[36] Kumar, B.R., et al., Artificial neural network model for prediction of rock properties from sound level produced during drilling. Geomechanics Geoengineering, 2013. 8(1): p. 53-61.
[37] Kumar, B.R., et al., Regression analysis and ANN models to predict rock properties from sound levels produced during drilling. International Journal of Rock Mechanics Mining Sciences, 2013. 58: p. 61-72.
[38] Kahraman, S., M. Delibalta, and R. Comakli, Noise level measurement test to predict the abrasion resistance of rock aggregates. Fluctuation Noise Letters2013 p. 1350021.
[39] Karakus, M. and S. Perez, Acoustic emission analysis for rock–bit interactions in impregnated diamond core drilling. International Journal of Rock Mechanics Mining Sciences, 2014. 68: p. 36-43.
[40] Flegner, P., et al., Measurement and processing of vibro-acoustic signal from the process of rock disintegration by rotary drilling. Measurement, 2014. 56: p. 178-193.
[41] Qin, M., et al., Analysis of signal characteristics from rock drilling based on vibration and acoustic sensor approaches. Applied Acoustics, 2018. 140: p. 275-282.
[42] Kong, X., et al., Critical slowing down on acoustic emission characteristics of coal containing methane. Journal of Natural Gas Science Engineering, 2015. 24: p. 156-165.
[43] Du, F., et al., Investigation on acoustic emission characteristics during deformation and failure of gas-bearing coal-rock combined bodies. Journal of Loss Prevention in the Process Industries, 2018.
[44] Yari, M. and R. Bagherpour, Implementing Acoustic Frequency Analysis for Development the Novel Model of Determining Geomechanical Features of Igneous Rocks Using Rotary Drilling Device. Geotechnical Geological Engineering, 2018. 36(3): p. 1805-1816.
[45] Yari, M. and R. Bagherpour, Investigating an innovative model for dimensional sedimentary rock characterization using acoustic frequency analysis during drilling. Rudarsko Geolosko Naftni Zbornik, 2018. 33(2): p. 17-25.
[46] Yari, M., R. Bagherpour, and M. Khoshouei, Developing a novel model for predicting geomechanical features of carbonate rocks based on acoustic frequency processing during drilling. Bulletin of Engineering Geology and the Environment, 2019. 78(3): p. 1747-1759.
[47] Liu, M.-K., Y.-H. Tseng, and M.-Q. Tran, Tool wear monitoring and prediction based on sound signal. The International Journal of Advanced Manufacturing Technology, 2019. 103(9): p. 3361-3373.
[48] Khoshouei, M., et al., A New Look at Hard Rock Abrasivity Evaluation Using Acoustic Emission Technique (AET). Rock Mechanics and Rock Engineering, 2022. 55(4): p. 2425-2443.