基于神经网络的加工过程模型辨识

Neural network based model identification of machining process

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。

Neural network architecture for dynamic modeling is introduced.Taking the turning process as an example, this investigates the identification of the nonlinear machining process using a backpropagation neural network with a single hidden layer, and compares the tracking response of the neural network model with that of the parameter model. Simulat ion resu1ts show that neural network is an effective approach to model nonlinear machining processes.