In-process Detection of Wear and Fracture of Wood Cutting Tool.

Research Project

Project/Area Number	60460208
Research Category	Grant-in-Aid for General Scientific Research (B)
Allocation Type	Single-year Grants
Research Field	林産学
Research Institution	Kyushu University
Principal Investigator	MORI Minoru Kyushu University, 農学部, 教授 (20038152)
Co-Investigator(Kenkyū-buntansha)	INOUE Hiroyuki Fukuoka University of Education, 教育学部, 助教授 (00036914) MURASE Yasuhide Kyushu University, 農学部, 助手 (50038288)
Project Period (FY)	1985 – 1986
Project Status	Completed (Fiscal Year 1986)
Budget Amount *help	¥7,200,000 (Direct Cost: ¥7,200,000) Fiscal Year 1986: ¥1,000,000 (Direct Cost: ¥1,000,000) Fiscal Year 1985: ¥6,200,000 (Direct Cost: ¥6,200,000)
Keywords	Wood Cutting / Acoustic Emission / In-process Detection / Tool Wear / 繊維傾斜角
Research Abstract	The in-process monitoring technique of cutting tool wear or cutting conditions is important for the automation of wood machining operation. In this study, the fundamental research on the in-process detecting method of cutting tool wear and surface finish have been carried out by making use of acoustic emission(AE). The results are summarized as follows: 1. The AE signal generated during cutting is comparatively similar to the continuous AE type. 2. The AE level for a worn tool decreases in comparison with that for a sharp tool. 3. The AE level increases with increasing depth of cut and remarkably with increasing cutting speed. 4. The AE count rate obtained by ringdown counting method is effective to characterize the AE signal generated during cutting. 5. The peak of AE signal is detected mainly in the frequency range at 0.1-0.3 MHz. 6. The AE signal generated during cutting against grain is remarkably high. From the above results, it was found that the AE signal was sensitive to changes in the tool wear and the slope angle of grain. Accordingly, the use of AE signal is promising for in process detection of tool wear or defects of cut surface(torn grain and chipped grain).