为解决送粉式金属直接成形过程中，会出现机械性能降低、多物理场耦合、机理复杂、工艺参数多、熔 池凝固速率较大等问题，设计一种基于神经网络PSD 算法的成形过程自适应成形闭环反馈控制系统。根据光学系统 实时监测激光熔池的图像信号，利用图像融合与视觉检测技术构造熔池图像特征集，对工艺参数与熔池尺寸动态关 系进行分析，构建成形质量精度辨识体系，通过神经网络PSD 算法优化，实现LMD 成形过程工艺参数的自适应控 制。仿真结果表明：该控制器对熔池宽度有较高的控制精度，可改善制造工艺成形质量和保证工艺稳定性。
In order to solve the problems of low mechanical properties, multi-physical field coupling, complex mechanism, many process parameters and high solidification rate of molten pool in powder feeding metal direct forming process, etc, a closed-loop feedback control system for adaptive forming process based on neural network PSD algorithm is designed. According to the real-time image signal of laser molten pool monitored by optical system, the image feature set of molten pool is constructed by image fusion and visual detection technology, the dynamic relationship between process parameters and molten pool size is analyzed and the precision identification system of forming quality is constructed. The adaptive control of process parameters in LMD forming process is realized by optimizing the PSD algorithm of neural network. The simulation results show that the adaptive controller has high control accuracy for the width of molten pool, and can obviously improve the forming quality of manufacturing process and ensure the stability of process.
刘广志.基于神经网络PSD 算法的LMD 自适应控制系统[J].,2020,39(06).复制