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基于人工神经网络建立变切削条件下的钻头磨损监控系统。以机床主轴和进给轴的电机功率（电流）信号为监控信号，并通过机床的速度向量识别机床的加工状态；通过对监控信号的提取和预处理，得到人工种经网络模型的输入（有效切谢功率和切削用量）；用3层BP网络对钻头的磨损量进行预报。
The Drill Wear Monitoring System Based on Artificial Neural Network under Variable Cutting Condition. The motor power (current) signal of the spindle and the feed axis of the machine tool is taken as the monitoring signal, and the processing state of the machine tool is identified by the speed vector of the machine tool. Through the extraction and preprocessing of the monitoring signal, the input of the artificial model via the network model Thanks to the power and cutting); 3-layer BP network to predict the amount of wear drill bit.