Detection of chipping in ceramic cutting inserts from workpiece profile during turning using fast Fourier transform (FFT) and continuous wavelet transform (CWT) |
| |
| Affiliation: | 1. School of Mechanical Engineering, Engineering Campus, Universiti Sains Malaysia, Seri Ampangan, 14300 Nibong Tebal, Penang, Malaysia;2. School of Materials and Mineral Resources Engineering, Engineering Campus, Universiti Sains Malaysia, Seri Ampangan, 14300 Nibong Tebal, Penang, Malaysia;1. Department of Mechanical Engineering, Tsinghua University, Beijing, China;2. College of Electronic Science, National University of Defense Technology, Hunan, China;3. Changzhou Institute of Technology, Jiangsu, China;4. School of Engineering, RMIT University, Melbourne, Australia;1. Dpto. de Ingenierías Mecánica, Informática y Aeroespacial - Universidad de León, Campus de Vegazana S/N 24071 León, Spain;2. Dpto. de Ingenierías Eléctrica y de Sistemas y Automática - Universidad de León, Campus de Vegazana S/N 24071 León;3. Neuroimaging Sciences - Centre for Clinical Brain Sciences, Chancellor''s Building 49 Little France Crescent Edinburgh EH16 4SB, Scotland;4. Second affiliation, Address, City and Postcode, Country;1. McMaster Manufacturing Research Institute (MMRI), Department of Mechanical Engineering, McMaster University, 1280 Main Street West, Hamilton, ON L8S4L7, Canada;2. Production Engineering Department, Alexandria University, Alexandria 21544, Egypt |
| |
| Abstract: | Ceramic cutting tool inserts are prone to premature failure by chipping instead of gradual wear due to their low impact toughness. Thus, in-process detection of failure of ceramic tools is important to prevent workpiece surface deterioration. The objective of this study is to develop a method of detection of the onset of chipping in ceramic cutting tool inserts during dry finish turning from the workpiece profile signature. The profile of the workpiece surface opposite the cutting side was captured using an 18-MP DSLR camera at a shutter speed of 0.25 ms during the turning of AISI01 oil-hardening tool steel. The edge profile was extracted to sub-pixel accuracy from the 2-D image of the workpiece surface using the invariant moment method. The effect of chipping in the ceramic insert on the surface profile signature of the workpiece was investigated using the fast Fourier transform (FFT) and continuous wavelet transform (CWT). The results show that the stochastic behavior of the cutting process after tool chipping manifest as sharp increase in the amplitude of spatial frequencies below the fundamental feed frequency. The proposed sub-window FFT method is effective in resolving the time resolution by detecting tool chipping at cutting time duration of around 17.13 s. Compared to the sub-window FFT method the CWT method is able to detect the exact onset of chipping in the cutting tool insert. |
| |
| Keywords: | FFT CWT Ceramic Tool chipping Workpiece profile |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
