基于熔池监测的激光沉积制造成形工艺参数的分析及预测

激光沉积制造(LDM)过程中,熔池宽度是成形精度的关键,主要受到工艺参数的影响。本文建立了基于CCD高速摄像机的熔池在线监测系统。为了提高熔池宽度检测精度,应用卡尔曼滤波技术对熔池宽度测量值进行了去噪处理。采用正交实验设计方法和多元回归分析,建立了熔池宽度与3个主要工艺参数(激光功率、扫描速度和送粉速率)间的关系模型。并设计单一变量实验对模型进行了验证。最后,利用粒子群算法(PSO)对薄壁结构的成形过程参数进行了预测。结果表明,对LDM成形过程进行工艺参数的分析和预测为实现沉积层成形精度的控制提供了依据。

Process parameters analysis and prediction during laser deposition manufacturing based on melt pool monitoring

During laser deposition manufacturing (LDM) process, melt pool width which is greatly influenced by process parameters is essential for the forming tracks geometry. In this paper, the melt pool geometry evolution was monitored by a CCD camera, and a method of applying Kalman filtering for the melt pool width detection during LDM process was presented to obtain accurate value. Orthogonal experimental design and multiple regression analysis were used to establish an empirical model describing the correlation between the melt pool width and three main process parameters (laser power, scanning speed, and powder feeding rate). And the developed model was verified experimentally. Finally, Particle swarm optimization (PSO) was implemented for prediction of process parameters during the buildup of a thin wall. The results indicate that process parameters analysis and prediction for LDM process could make it possible to acquire an efficient process for the forming tracks geometry control.