基于铣削声音信号的刀具状态实验研究

为了更加准确、有效对铣刀磨损状态进行监测，笔者提出以铣削声音为监测信号的方案，搭建基于铣削声音信号 的刀具状态监测平台，设计了基于LabVIEW的实验数据采集分析系统软件平台，并通过小波变换对实验结果进行了论 证。实验结果表明，在1.5～2．O kHz，2.5~4.5 kHz频率范围内，铣削声音信号与刀具磨损有很好的相关性；切削参数的 变化也会对声音信号产生影响，其中主轴转速的影响最为明显。方案验证了用声音信号监测刀具状态是切实可行的，为 刀具状态的监测提供了新的思路与方法。

Experimental Study on Tool Condition in Milling Based on Sound Signal

ln order to monitor the wear condition of milling cutter more accurately and effectively, a scheme was proposed to choose the milling sound signal as the monitoring signal. A tool condition monitor platform was established based on milling sound signal. A software platform based on LabVIEW was designed to deal with experimental data, including acquisition and analysis. And the results were demonstrated by wavelet transform. Experimental results showed that sound signal and tool wear had good correlation in the frequency range of l.5 kHz t0 2 kHz and 2.5 kHz t0 4.5 kHz;the change of cutting parameters would also affect the sound signal, the effect of spindle speed on sound signal was the most obviousmaxirnum. The scheme proved that it was feasible to monitor tool condition with sound signal, and provided a new idea and method for tool detection.