Application of image and sound analysis techniques to monitor the condition of cutting tools

Abstract Tool wear dramatically affects the texture of the machined surface and the sound generated by the cutting process. This paper discusses our work on texture analysis of machined surfaces and signal processing of sound generated by machining process and investigates the correlation between tool wear and quantities characterizing machined surfaces and sound pattern. Our results clearly indicate that tool condition monitoring which is defined as the ability to distinguish between a sharp, a semi-dull, or a dull tool can be successfully accomplished by combining sensory data from a CCD camera (image analysis) and a microphone (sound analysis).

[1]  Anil K. Jain.  Fundamentals of Digital Image Processing , 2018, Control of Color Imaging Systems.

[2]  Hidehiko Takeyama,et al.  In-Process Detection of Surface Roughness in Machining , 1977 .

[3]  Paul Vanherck,et al.  Assessment of surface typology analysis techniques , 1979 .

[4]  Youmin Zhang,et al.  A new clustering and training method for radial basis function networks , 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

[5]  D. Spurgeon,et al.  In-Process Indication of Surface Roughness Using a Fibre-Optics Transducer , 1975 .

[6]  J. Tlusty,et al.  A Critical Review of Sensors for Unmanned Machining , 1983 .

[7]  B. Lindström,et al.  A flexible real-time adaptive control system for turning , 1991 .

[8]  D. J. Whitehouse,et al.  Surfaces — A Link between Manufacture and Function: , 1978 .

[9]  Jean-Michel Poggi,et al.  Wavelet Toolbox User s Guide , 1996 .

[10]  G. Chryssolouris,et al.  Developments and Trends in Monitoring and Control of Machining Processes , 1988 .

[11]  James F. Greenleaf,et al.  Use of gray value distribution of run lengths for texture analysis , 1990, Pattern Recognit. Lett..

[12]  C. Chui,et al.  Wavelets : theory, algorithms, and applications , 1994 .

[13]  Ichiro Inasaki,et al.  Tool Condition Monitoring (TCM) — The Status of Research and Industrial Application , 1995 .

[14]  Rangachar Kasturi,et al.  Machine vision , 1995 .

[15]  F Giusti,et al.  A Flexible Tool Wear Sensor for NC Lathes , 1984 .

[16]  H.J.J. Kals,et al.  Developments and Trends in Monitoring and Control of Machining Processes , 1988 .

[17]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Jooyoung Park,et al.  Universal Approximation Using Radial-Basis-Function Networks , 1991, Neural Computation.

[19]  Stephen A. Dyer,et al.  Digital signal processing , 2018, 8th International Multitopic Conference, 2004. Proceedings of INMIC 2004..