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介绍了神经网络动态建模方法，以车削加工过程为例，用一个带单隐层的反向传播（BP）网络对非线性的加工过程进行了辨识研究，并将神经网络模型的跟踪响应与参数模型的跟踪响应作了对比分析。仿真结果表明，神经网络是建立非线性加工过程模型的一种有效方法。
The method of dynamic modeling of neural network is introduced. Taking a turning process as an example, a nonlinear backpropagation (BP) network with a single hidden layer is used to identify the nonlinear machining process. The tracking response of the neural network model and Parametric model of the tracking response made a comparative analysis. The simulation results show that the neural network is an effective method to establish the nonlinear machining process model.