中文摘要：

通过一套基于虚拟仪器的信号采集系统，采集高速干铣削铝合金过程中的温度信号、声发射信号和振动信号。对温度信号进行小波变换后，发现随着进给量的增加，刀尖附加切削区域的温度反而降低。对声发射信号和振动信号进行小波包分解后，用各频段小波包系数的能量百分比构造一个特征向量，发现高速干铣削过程中代表加工稳定因素的低频部分能量占总能量的百分比较高。

英文摘要：

The temperature, acoustic emission （AE） and vibration signals in the process of high speed dry milling aluminum alloy were gathered by a signal gathering system based on LabVIEW environment. The temperature signals were processed by the wavelet transform and show that temperature decreases as the machining feed increases. And then the AE and vibration signals were processed by wavelet package transform, A characteristic vector was constructed by the energy of different frequency segment, which was calculated by using the coefficient of wavelet package transform of the AE and vibration signals. The vector shows that the energy of low frequency segment is of the majority of the total energy, the low frequency segment is regarded as a stable factor in machining.