[1] CHEN Y, YANG SH B, FU Y C, et al.. FEM estimation of tool wear in high speed cutting of Ti6Al4V alloy [J]. Acta Aeronautica et Astronautica Sinica, 2013, 34(9): 2230-2240. (in Chinese)
[2] LIANG W Y, GUO J K, CHEN X B, et al.. Research and application of end mill wear state measuring system based on shadow casting [J]. Tool Engineering, 2012,46(12): 59-74. (in Chinese)
[3] BRADLEY C, WONG Y S. Surface texture indicators of tool wear - a machine vision [J]. The International Journal of Advanced Manufacturing Technology, 2001, 17(6): 435-443.
[4] SUN L L, LI Y, ZHENG J M, et al.. Fractal analysis of PCA reconstruction for tool wear monitoring [J]. Mechanical Science and Technology for Aerospace Engineering, 2010, 29(3): 395-397. (in Chinese)
[5] YANG J G, XIAO R, LI B ZH, et al.. Tool wear detection based on machine vision [J]. Journal of Donghua university, 2012,38(5): 505-508, 518. (in Chinese)
[6] HUSSAIN S, CHEN X. Remote milling tool-wear monitoring and direct wear features extraction by image processing [J]. Internet Manufacturing and Services, 2008, 1(3): 246-261.
[7] JURKOVIC J, KOROSEC M, KOPAC J. New approach in tool wear measuring technique using CCD vision system [J]. International Journal of Machine Tools & Manufacture, 2005, 45(9): 1023-1030.
[8] MOOK W K, SHAHABI H H, RATNAM M M. Measurement of nose radius wear in turning tools from a single 2D image using machine vision [J]. The International Journal of Advanced Manufacturing Technology, 2009, 43(3-4): 217-225.
[9] ZHANG J L, ZHANG C, GUO S, et al.. Research on tool wear detection based on machine vision in end milling process [J]. Production Engineering, 2012,6(4-5): 431-437.
[10] CASTEJON M, ALEGRE E, BARREIRO J, et al.. On-line tool wear monitoring using geometric descriptors from digital images [J]. International Journal of Machine Tools & Manufacture, 2007, 47(18): 1847-1853.