Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-27T08:01:56.987Z Has data issue: false hasContentIssue false

Application of the cyclostationairity for the cutting tooldiagnosis

Published online by Cambridge University Press:  26 September 2014

Khalid Ait-Sghir*
Affiliation:
Groupe de Recherche en Science Pour l’Ingénieur, Université de Reims Champagne Ardenne, UFR Sciences Exactes et Naturelles, Moulin de la Housse, BP 1039, 51687 Reims Cedex 2, France
Mohamed El badaoui
Affiliation:
Université de Lyon, Université Jean Monnet de Saint Etienne, Campus Roannais, Laboratoire d’Analyse des Signaux et des Processus Industriels (LASPI), 42300 Roanne, France
François Guillet
Affiliation:
Université de Lyon, Université Jean Monnet de Saint Etienne, Campus Roannais, Laboratoire d’Analyse des Signaux et des Processus Industriels (LASPI), 42300 Roanne, France
Driss Aboutajdine
Affiliation:
Faculté des sciences, Université Mohammed V-Agdal, 4 avenue Ibn Battouta, Rabat, Maroc
Jean-Paul Dron
Affiliation:
Groupe de Recherche en Science Pour l’Ingénieur, Université de Reims Champagne Ardenne, UFR Sciences Exactes et Naturelles, Moulin de la Housse, BP 1039, 51687 Reims Cedex 2, France
*
a Corresponding author:khalid.ait-sghir@univ-reims.fr
Get access

Abstract

This work is interested to the analysis of the vibratory signals coming from a millingoperation. The objective is the detection of cutting tool breakage using thecyclostationary tools. Initially, we will show that the vibration signals captured fromthe milling operation are cyclostationary. The proposed cyclostationary methods are thefirst and second order synchronous statistics and the spectral correlation. A test rig,composed of a milling machine (cutter with 5 teeth) and a workpiece, is used to extractthe vibration signals that are angular sampled in the free fault case and one broken toothcase. This test rig is instrumented with three accelerometers, installed in the threedirections, and an optical encoder that allows the angular sampling. Then we will see thatthe angular sampling of the signals captured from a milling operation is essential topreserve the cyclostationary properties destroyed, in the case of the temporal sampling,by speed fluctuations. The proposed method capacity to detect the broken tooth is shown.The synchronous statistics of order 1 and order 2 detect the broken tooth presence and itsemplacement. The spectral correlation analysis distinguishes the broken tooth presence,but is not practical for the diagnosis. For that, an indicator based on the spectralcorrelation is proposed.

Type
Research Article
Copyright
© AFM, EDP Sciences 2014

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Byrne, G., Dornfeld, D., Inasaki, I., Ketteler, G., König, W., Teti, R., Tool Condition Monitoring (TCM) – The Status of Research and Industrial Application, CIRP Annals: Manuf. Technol. 44 (1995) 541567 CrossRefGoogle Scholar
Yeo, S.H., Khoo, L.p., Neo, S.S., Tool condition monitoring using reflectance of chip surface and neural network, J. Intelligent Manuf. 11 (2000) 507514 CrossRefGoogle Scholar
Kurada, S., Bradeley, C., A review of machine vision sensors for tool condition monitoring, Comput. Ind. 34 (1997) 5572 CrossRefGoogle Scholar
Rehorn, A.G., Jiang, J., Orban, P.E., State-of-the-art methods and results in tool condition monitoring: a review, Int. J. Adv. Manuf. Technol. 26 (2005) 693710 CrossRefGoogle Scholar
Kegg, R.L., On-line machine and process diagnostics, CIRP Annals: Manuf. Technol. 33 (1984) 469473 CrossRefGoogle Scholar
Huang, S.N., Tan, K.K., Wong, Y.S., de Silva, C.W., Goh, H.L., Tan, W.W., Tool wear detection and fault diagnosis based on cutting force monitoring, Int. J. Mach. Tools Manuf. 47 (2007) 444451 CrossRefGoogle Scholar
Kuljanic, E., SortinoTWEM, M., a method based on cutting forces–monitoring tool wear in face milling, Int. J. Mach. Tools Manuf. 45 (2005) 2934 CrossRefGoogle Scholar
Alonso, F.J., Salgado, D.R., Analysis of the structure of vibration signals for tool wear detection, Mech. Syst. Signal Process. 22 (2008) 735748 CrossRefGoogle Scholar
Orhan, S., Osman, A., Camuscu, N., Aslan, E., Tool wear evaluation by vibration analysis during milling of AISI D3 cold work tool steel with 35 HRC hardness, NDTE&E Int. 40 (2007) 11126 Google Scholar
Dimla, D.E., Sensor signals for tool-wear monitoring in metal cutting operations–a review of methods, Int. J. Mach. Tools Manuf. 40 (2000) 10731098 CrossRefGoogle Scholar
Lin, J., Inverse estimation of the tool-work interface temperature in end milling, Int. J. Mach. Tools Manuf. 35 (1995) 751760 CrossRefGoogle Scholar
Srinivasa Pai, P., Ramakrishna Rao, P.K., Acoustic emission analysis for tool wear monitoring in face milling, Int. J. Prod. Res. 40 (2002) 10811093 Google Scholar
Gardner, W.A., Stationarizable Random Processes, IEEE Trans. Inf. Theory 24 (1978) 822 CrossRefGoogle Scholar
W.A. Gardner, Statistical Spectral analysis: a non probabilistic theory, Prentice, Hall Inc, 1988
Capdessus, C., Sidahmed, M., Lacoume, J.L., Cyclostationary processes, application in gear faults early diagnosis, Mech. Syst. Signal Process. 14 (2000) 37138 CrossRefGoogle Scholar
Antoni, J., Bonnardot, F., Raad, A., Elbadaoui, M., Cyclostationnary modelling of rotating machine vibration signals, Mech. Syst. Signal Process. 18 (2004) 12851314 CrossRefGoogle Scholar
J. Antoni, Apports de l’échantillonnage angulaire et de la cyclostationnarité au diagnostic par analyse vibratoire des moteurs thermiques, Thèse de l’Institut national polytechnique de Grenoble, 2000
Antoni, J., Cyclic spectral analysis in practice, Mech. Syst. Signal Process. 21 (2007) 597630 CrossRefGoogle Scholar
Elbestawi, M.A., Papazariou, T.A., Du, R.X., In process monitoring of tool wear in milling using cutting force signature, Int. J. Mach. Tools Manuf. 31 (1991) 5573 CrossRefGoogle Scholar
F. Bonnardot, Comparaison entre les analyses angulaire et temporelle des signaux vibratoires de machines tournantes. Etude du concept de cyclostationnarité floue, Thèse de l’Institut national polytechnique de Grenoble, 2004
Randall, R.B., Antoni, J., The relationship between spectral correlation and envelope analysis in the diagnostics of bearing faults and other cyclostationary machine signals, Mech. Syst. Signal Process. 15 (2001) 945962 CrossRefGoogle Scholar