基于BP网络预测高速铣削加工薄铝制件尺寸误差的动态分布

Forecasting Dynamic Distribution of Errors for High Speed Milling Super-thin Aluminium Parts Based on BP Neural Network

为了有效控制高速铣削加工超薄铝合金零件工艺过程,保证工件的加工质量和提高加工效率,需要及时掌握加工过程尺寸分布及其变化规律。为此,提出一种基于人工神经网络预测高速铣削加工超薄铝合金零件尺寸误差动态分布的方法,该方法在实际应用中取得了满意的效果。

It＇s necessary to monitor the dynamic distribution and variation regularity of dimension in time in order to effectively control the machining process of high speed milling for super-thln Aluminium parts, assure the product quality and enhance work efficiency. A method of forecasting the dynamic distribution of machining dimension errors based on BP neural network was proposed. The method was verified effectively in practice.