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Measurement, modeling and evaluation of surface parameter using capacitive-sensor-based measurement system

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Surface roughness parameter prediction and evaluation are important factors in determining the satisfactory performance of machined surfaces in many fields. The recent trend towards the measurement and evaluation of surface roughness has led to renewed interest in the use of newly developed non-contact sensors. In the present work, an attempt has been made to measure the surface roughness parameter of different machined surfaces using a high sensitivity capacitive sensor. A capacitive response model is proposed to predict theoretical average capacitive surface roughness and compare it with the capacitive sensor measurement results. The measurements were carried out for 18 specimens using the proposed capacitive-sensor-based non-contact measurement setup. The results show that surface roughness values measured using a sensor well agree with the model output. For ground and milled surfaces, the correlation coefficients obtained are high, while for the surfaces generated by shaping, the correlation coefficient is low. It is observed that the sensor can effectively assess the fine and moderate rough-machined surfaces compared to rough surfaces generated by a shaping process. Furthermore, a linear regression model is proposed to predict the surface roughness from the measured average capacitive roughness. It can be further used in on-machine measurement, on-line monitoring and control of surface roughness in the machine tool environment.
Rocznik
Strony
403--418
Opis fizyczny
Bibliogr. 28 poz., rys., tab., wykr.
Twórcy
autor
  • Manufacturing Engineering Section, Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai-600 036, India, murugarajan01@hotmail.com
Bibliografia
  • [1] Jiang, X., Scott, P.J., Whitehouse, D.J., Blunt, L. (2007). Paradigm shifts in surface metrology. Part I. Historical Philosophy, Proceedings of Royal Society A, 463, 2049-2070.
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  • [3] Uchida, S., Sato, H., O-hori, M. (1979). Two dimensional measurement of surface roughness by the light sectioning method, Annals CIRP, 28(1), 419-423.
  • [4] Bjuggren, M., Krummenacher, L., Mattsson, L. (1997). Noncontact surface roughness measurement of engineering surfaces by total integrated infrared scattering, Precision Engineering, 20(1), 33-45.
  • [5] Toh, S.L., Shang, H.M., Tay, C.J. (1998). Surface-roughness study using laser speckle method, Optics and Lasers in Engineering, 29(2-3), 217-225.
  • [6] Cahill, B., El Baradie M.A. (2001). LED-based fibre-optic sensor for measurement of surface roughness, Journal of Materials Processing Technology, 119(1-3), 299-306.
  • [7] Kohno, T., Ozawa, N., Miyamoto, K., Musha, T. (1988). High precision optical surface sensor, Applied Optics, 27(1), 103-108.
  • [8] Bradley, C., Bohlmann, J., Kurada, S. (1998). A fiber optic sensor for surface roughness measurement, Journal of Manufacturing Science and Engineering, 120(2), 359-367.
  • [9] Luk, F., Hyunh, V., North, W. (1989). Measurement of surface roughness by a machine vision system, Journal of Physics E: Scientific Instruments, 22 (12), 977-980.
  • [10] Al-Kindi, G.A., Baul, R.M., Gill, K.F. (1992). An application of machine vision in the automated inspection of engineering surfaces, International Journal of Production Research, 30(2), 241-253.
  • [11] Kiran, M.B., Ramamoorthy, B., Radhakrishnan,V. (1998). Evaluation of surface roughness by vision system, International Journal of Machine Tools and Manufacture, 38(5-6), 685-690.
  • [12] Dhanasekar, B., Ramamoorthy, B. (2006). Evaluation of surface roughness using a image processing and machine vision system, Journal of Metrology Society of India, 21(1), 9-15.
  • [13] Zawada-Tomkiewicz, A. (2010). Estimation of surface roughness parameter based on machined surface image, Metrology and Measurement Systems, 17(3), 493-504.
  • [14] Adamczak, S., Makieła, W., Stępień, K. (2010). Investigating advantages and disadvantages of the analysis of a geometrical surface structure with the use of Fourier and wavelet transform, Metrology and Measurement Systems, 17(2), 233-244.
  • [15] Shin, Y.C., Oh, S.J., Coker, S.A. (1995). Surface roughness measurement by ultrasonic sensing for inprocess monitoring, Transactions ASME: Journal of Engineering for Industry, 117(3), 439-447.
  • [16] Sherwood, K.E., Crookall, J.K. (1967-68). Surface finish assessment by electrical technique, Proceedings of Institution of Mechanical Engineers E (London), 182(3k), 344-349.
  • [17] Brecker, H.N., Fromson, R.N., Shum, L.Y. (1977). A capacitance based surface texture measuring system, Annals of the CIRP, 25(1), 375-377.
  • [18] Shunmugam, M.S., Deshpande, G.N. (1980). Inductive and capacitive measurements of surface finish, Proceedings of the 9th AIMDTR Conference-1980, IIT-Kanpur, India, 439-442.
  • [19] Lieberman, A.G., Vorburger, T.V., Giauque, C.H.W., Risko, D.G., Resnick, R., Rose, J.(1988). Capacitance versus stylus measurement of surface roughness, Surface Topography, 1, 315-330.
  • [20] Garbini, J.L., Koh, S., Jorgensen, J.E., Ramulu, M. (1992). Surface profile measurement during turning using fringe-field capacitive profilometry, Transactions of the ASME: Journal of Dynamic system, Measurement and Control, 114 (2), 234-243.
  • [21] Nowicki, B., Jarkiewicz, A. (1998). The in-process surface roughness measurement using fringe field capacitive (FFC) method, International Journal of Machine Tools and Manufacturing, 38 (5-6), 725-732.
  • [22] Williams, R.E., Rajurkar, K.P., Bishu, R.R. (1990). Experimental comparison of a stylus based and a capacitance based surface roughness measurement system for different micro surface contour, Society of Manufacturing Engineers, IQ990-255, 1-13.
  • [23] Varghese S., Radhakrishnan, V. (1994). A multi sensor approach to in-process monitoring of surface roughness, International Journal of Material Processing Technology, 44(3-4), 353-362.
  • [24] Kiyono, S, Gao, W. (1994). Profile measurement of machined surface with a new differential method, Precision Engineering, 16(3), 212-218.
  • [25] Guadarrama-Santana, A, Garcia-Valenzuela, A., Bruce, N.C. Cordero, J. (2003). A new approach for measuring surface parameters by a capacitive sensor, Sensors: Proceedings of IEEE, 1, 553-558.
  • [26] Bruce, N.C., García-Valenzuela, A. (2005). Capacitance measurement of Gaussian random rough surfaces with planar and corrugated electrodes, Measurement Science and Technology, 16(3), 669-676.
  • [27] Chang, H.-K., Kim, J.-H., Kim, I.H., Jang, D.Y., Han, D.C. (2007). In-process surface roughness prediction using displacement signals from spindle motion, International Journal of Machine Tools and Manufacture, 47 (6), 1021-1026.
  • [28] Lion precision, Technote (2009). Capacitive sensor operation and optimization, LT-03-0020.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSW1-0083-0006
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