Ni基-WC合金粉末激光熔覆层形貌的预测

摘要

Based on BP neural network , network model used for predicting laser fuse cladding appearance and size has been established, further correspondence between characteristic signals of laser fuse cladding (ultraviolet emission, infrared emission and audible sound ) and laser fuse cladding appearance (fuse cladding height&width) has been re-searched.The result showed that the network model prediction was provided with lower mean error and higher test pre -cision and possessed better prediction capability .%基于BP神经网络，建立网络模型对激光熔覆层形貌尺寸进行预测，研究激光熔覆特征信号（蓝紫光信号、红外辐射信号、可听声信号）和激光熔覆形貌（熔覆层高、宽）之间的对应关系。结果表明，该网络模型预测平均误差小，检验精度高，具有较好的预测能力。