基于SAPSO-BP的薄壁件侧铣加工变形预测方法研究

Research on the deformation prediction method based on SAPSO-BP thin-wall workpiece side milling

针对薄壁件在侧铣加工过程中容易产生让刀变形的问题,为实现薄壁件侧铣加工方式下变形量的预测,提出了一种基于SAPSO-BP神经网络技术预测薄壁件侧铣加工变形的方法。通过建立T型薄壁件侧铣加工仿真模型,并用实验验证其有效性,为后续神经网络提供训练样本;再引入模拟退火粒子群算法(SAPSO),优化BP神经网络的初始权值与阈值,建立基于SAPSO-BP的薄壁件侧铣加工变形预测模型,并验证分析了其可行性。

In order to predict the deformation of thin-walled parts during side milling,a new method based on SAP-SO-BP neural network is proposed to predict the deformation of thin-walled parts in side milling.Through the establishment of T-shaped thin-walled workpiece side milling simulation model,and experimental verification of its feasibility,provide training samples for the follow-up neural network;then introduce simulated annealing particle swarm optimization(SAPSO)to optimize the initial weights and thresholds of BP neural network,establish the deformation prediction model of thin-walled workpiece side milling based on SAPSO-BP,and verify and analyze its reliability.