基于图像处理和LIPS分析的金属表面激光清洗过程监控

Laser Cleaning Process Monitoring of Metal Surface Based on Image Processing and LIPS Analysis

激光清洗过程监控是准确去除金属锈蚀层、有效避免金属基体损伤的关键。利用图像处理技术研究了30 mm×30 mm较大面积Q235B钢板在不同光斑搭接率下的清洗次数与清洗度的变化规律,得到50%的最佳光斑搭接率。利用激光诱导等离子体光谱研究了0.47 mm×0.47 mm微小面积Q235B钢板的皮尔逊相关系数随清洗次数的变化趋势,得到了不同厚度锈蚀层下的最佳清洗次数。在此基础上,将图像处理法与LIPS分析法协同使用,利用LIPS分析法能够根据微小面积锈蚀层厚度不同而动态校正最小清洗次数的特点,弥补了图像处理法无法精确控制激光清洗过程的缺陷,99.1%的清洗度表明两种方法的协同使用可对Q235B钢板大面积激光清洗过程进行有效监控。

Laser cleaning processing monitoring is essential to accurately remove the rust layer and effectively avoid the damages of the metal substrate.The variations between the number of cleaning and the rust cleaning rate at different spot overlap ratios on 30 mm×30 mm Q235B steel plate were studied by image processing to obtain the optimum spot overlap ratio of 50%.The changing trends of the Pearson correlation coefficient following the number of cleaning on 0.47 mm×0.47 mm Q235B steel plate were studied by Laser-induced Plasma Spectroscopy(LIPS)and the optimum number of cleaning was obtained under different thick dust layer.On this basis,the cooperation of image processing and LIPS is not only to dynamically correct the optimum number of cleaning but also to cover the shortage that image processing can not control the process of laser cleaning accurately.The results show that the cooperation of two methods can monitor the process of laser cleaning on a large area of Q235B steel plate and achieve high-quality laser cleaning with a 99.1%cleaning rate.