[1]
D. E. D. Snr, Sensor signals for tool-wear monitoring in metal cutting operations—a review of methods, International Journal of Machine Tools and Manufacture,40 (2000) 1073-1098.
DOI: 10.1016/s0890-6955(99)00122-4
Google Scholar
[2]
A. OUAHABI, W. Rmili, and R. Serra, Analyse temps-fréquence appliquée aux signaux vibratoires relevés en tournage, Congrès français de mécanique, (2007).
Google Scholar
[3]
A. Siddhpura and R. Paurobally, A review of flank wear prediction methods for tool condition monitoring in a turning process,The International Journal of Advanced Manufacturing Technology, 65 (2013) 371-393.
DOI: 10.1007/s00170-012-4177-1
Google Scholar
[4]
A. González-Laguna, J. Barreiro, A. Fernández-Abia, E. Alegre, and V. González-Castro, Design of a TCM system based on vibration signal for metal turning processes, Procedia engineering, 132 (2015) 405-412.
DOI: 10.1016/j.proeng.2015.12.512
Google Scholar
[5]
D. E. Dimla, The correlation of vibration signal features to cutting tool wear in a metal turning operation," The International Journal of Advanced Manufacturing Technology, 19 (2002) 705-713.
DOI: 10.1007/s001700200080
Google Scholar
[6]
M. K. Babouri, N. Ouelaa, and A. Djebala, Evolution et estimation de l'usure des outils de coupe en usinage, Evolution, 20 (2010) 21.
Google Scholar
[7]
W. Rmili, R. Serra, and A. Ouahabi, Contribution à l'étude de la surveillance de l'usure des outils de coupe en usinage, Congrès français de mécanique, (2007).
Google Scholar
[8]
M. K. Babouri and N. Ouelaa, Application de l'Analyse Multirésolution en Ondelettes Pour la Prédiction de l'Usure des Outils de Coupe,(2010).
Google Scholar
[9]
H. Chelladurai, V. Jain, and N. Vyas, Development of a cutting tool condition monitoring system for high speed turning operation by vibration and strain analysis, The International Journal of Advanced Manufacturing Technology,37 (2008) 471-485.
DOI: 10.1007/s00170-007-0986-z
Google Scholar
[10]
M. K. Babouri, N. Ouelaa, A. Djebala, M. C. Djamaa, and S. Boucherit, Prediction of cutting tool's optimal lifespan based on the scalar indicators and the wavelet multi-resolution analysis, Applied Mechanics, Behavior of Materials, and Engineering Systems, ed: Springer, (2017) 299-310.
DOI: 10.1007/978-3-319-41468-3_24
Google Scholar
[11]
R. Serra, W. RMILI, and A. OUAHABI, Suivi de l'usure des outils de coupe en tournage à sec de la fonte FT25 par analyse vibratoire, Congrès français de mécanique (2009).
Google Scholar
[12]
E. G. Plaza and P. N. López, Analysis of cutting force signals by wavelet packet transform for surface roughness monitoring in CNC turning, Mechanical Systems and Signal Processing, 98 (2018) 634-651.
DOI: 10.1016/j.ymssp.2017.05.006
Google Scholar
[13]
M. K. Babouri, N. Ouelaa, and A. Djebala, Experimental study of tool life transition and wear monitoring in turning operation using a hybrid method based on wavelet multi-resolution analysis and empirical mode decomposition, The International Journal of Advanced Manufacturing Technology, 82 (2016) 2017-2028.
DOI: 10.1007/s00170-015-7530-3
Google Scholar
[14]
S. Dutta, S. K. Pal, and R. Sen, Progressive tool flank wear monitoring by applying discrete wavelet transform on turned surface images,Measurement, 77 (2016) 388-401.
DOI: 10.1016/j.measurement.2015.09.028
Google Scholar
[15]
S. Mallat, A wavelet tour of signal processing: Elsevier, (1999).
Google Scholar
[16]
M. Babouri, N. Ouelaa, and A. Djebala, Temporal and frequential analysis of the tools wear evolution, Mechanics, 20 (2014) 205-212.
DOI: 10.5755/j01.mech.20.2.6933
Google Scholar
[17]
P. Huang, J. Li, J. Sun, and J. Zhou, Vibration analysis in milling titanium alloy based on signal processing of cutting force, The International Journal of Advanced Manufacturing Technology, 64 (2013) 613-621.
DOI: 10.1007/s00170-012-4039-x
Google Scholar
[18]
A. P. Rodrigues and G. DaAZMello, Selection of mother wavelet for wavelet analysis of vibration signals in machining, Journal of Mechanical Engineering and Automation, 6 (2016) 81-85.
Google Scholar