The AE signals of tool conditions were decomposed using a recursive wavelet from which the features were extracted and delivered to the wavelet network for fault recognition, and the recognition rate is up to 100%.

• 最后,对刀具AE信号进行递归小波分解,提取特征并应用小波网络识别刀具状态,识别率达到100%25。