粉末激光熔覆熔池行为的视觉监测与特征提取

Vision detection and feature extraction of molten pool behavior in powder laser cladding

熔池监测是激光熔覆工艺优化的基础,对提高激光熔覆成形质量至关重要。针对激光熔覆工艺建立了熔池视觉监测系统,基于OpenCV软件库提出K-means图像分割与双阈值Otsu图像分割相结合的方法,实现熔池与羽流的准确区分,提取熔池轮廓几何特征的准确率高达95%。通过设计正交实验激光熔覆Ti6Al4V金属粉末,选取典型熔覆试样对熔池的宽度及形态变化进行时域分析,得到熔覆层的熔池波动规律。结果表明:熔池的波动频率和幅度受工艺参数及其组合的影响,并随熔覆的进行逐渐趋于稳定。熔覆过程中熔池的异常波动利于熔覆缺陷的定位和识别,有助于优化工艺路线。

Molten pool monitoring is the basis of forming process optimization,playing a pivotal role in improving the formation quality.A machine vision monitoring system was set up for the laser cladding process.Based on the OpenCV software library,a method combining K-means image segmentation and dual threshold Otsu image segmentation was proposed,which realizes the accurate distinction between molten pool and plume with the accuracy of extracting geometric features of molten pool contour up to 95%.By designing an orthogonal experiment of laser cladding Ti-6Al-4V metal powder,typical cladding samples were selected to analyze the width and shape change of the weld pool in time domain,obtaining the fluctuation rule of the weld pool of the cladding layer.The results show that the fluctuation frequency and amplitude of the molten pool are affected by the process parameters and their combinations,and gradually stabilize with the progress of the cladding.Abnormal fluctuations in the molten pool during the cladding process are conducive to the positioning and identification of cladding defects,helping to optimize process routes.