刀具状态监测是实现自动化加工和无人化加工的关键技术。
Tool condition monitoring is the key technique in automatic and unmanned machining process.
为了有效的进行刀具状态监测，采用小波神经网络的松散型结合对刀具进行故障诊断。
In order to improve cutting tool condition monitoring, a method of cutting tool fault diagnosis based on wavelet and artificial networks with relaxed structure is proposed in this paper.
本文通过集成多个传感器的信息，建立了一个基于神经网络的刀具状态监测的智能系统。
This paper establishes an intelligent system based on Unsupervised neural network for monitoring the state of cutting tool by integrating information from a variety of sensors.
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