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

刀具磨损或切削状态的在线监测技术是实现木材加工作业自动化的重要手段。本文利用声发射技术对刀具磨损和表面光洁度的在线检测方法进行了基础性研究，主要研究结果如下：1.加工过程中产生的声发射信号与连续声发射信号较为相似。与锋利刀具相比，磨损刀具的声发射水平降低。声发射强度随切割深度的增加而增加，随切割速度的增加而显著增加。振荡法得到的声发射计数率能有效地表征切割过程中产生的声发射信号。5.声发射信号的峰值主要出现在0.1-0.3 MHz的频率范围内。结果表明，切割过程中产生的声发射信号对刀具磨损和磨粒倾角的变化非常敏感。因此，声发射信号在刀具磨损或切削表面缺陷(撕裂、切屑)检测中具有广阔的应用前景。

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).