基于神经网络的刀具振动趋势预测研究

Research on Cutter Vibration Trend Forecast based on Neural Network

在机床加工中，刀具的振动往往给工件带来负面影响。因此，研究刀具振动趋势就显得尤为重要。振动信号预测可看作是时间序列预测，故在MATLAB中，采用BP和RBF神经网络分别建立了非线性预测模型对其进行预测。结果表明，RBF网络有更好的预测精度。

In the machine processing, cutter vibration usually have a negative effect on the workpiece. Therefore, the research on the trend of cutter vibration is particularly important. The forecast for vibration signals is consider as time -series forecasting. So The BP and RBF neural network were adopted to establish nonlinear models for predicting a time series. The results show that the RBF neural network has higher accuracy.