摘要
提出了一个将小波包分析方法、模糊理论及人工神经网络技术相结合的智能刀具状态在线监测系统。系统利用小波包方法将声发射信号分解为不同频带的时间序列 ,从中抽取出与刀具切削状态紧密相关的序列信号的构方根值 (RMS)作为信号特征值。为了表示刀具状态与特征值之间的关系提出了一个模糊神经网络模型 ,采用了自组织竞争学习与BP算法相结合的混合学习算法。可迅速。
The tool condition directly affects the quality of workpiece and machining efficiency, and in the real time monitoring process of machining, it is the important factor of implement of intelligent manufacturing. Consequently, an on line intelligent monitoring system of tool condition that integrates wavelet packet transforma fuzzy theory and artificial neural network(ANN)is brought forward. A FNN model isput forward for showing the relation beween tool condition nd features, the model adopt hybrid liarning algorithm that integrates self organized competition learning and BP algorithm.
出处
《高技术通讯》
CAS
CSCD
2001年第1期81-84,13,共5页
Chinese High Technology Letters
基金
国防科工委资助项目
