针对传统除锈工艺在桥梁养护中的一些问题,进行了激光智能除锈的工艺及设备研究。为实现智能识别工件表面锈迹及除锈,采用Python及OpenCV视觉库对16Mn钢表面锈迹进行识别,通过一系列图像处理算法识别出生锈区域,得到生锈区域的位置信息、生锈等级、尺寸信息等,随后使用100 W激光除锈系统对识别出的锈迹进行清除,并对除锈后的工件再次进行识别检测。应用机器视觉辅助的激光去除锈蚀系统后,16Mn表面C、O元素的质量分数下降至5%以下。机器视觉辅助下的激光智能除锈可以快速、高效地识别出工件表面的锈蚀,并利用视觉算法和工艺数据库快速匹配相应的加工工艺参数,从而提高了加工效率、降低了人工成本。

In view of some problems of the traditional rust removal process in bridge maintenance, the laser intelligent rust removal process and equipment are studied in this work. To realize intelligent identification of rust on surfaces of workpieces and rust removal, first, the Python and OpenCV visual library are used to identify the rust on the 16Mn surface. A series of image processing algorithms are used to recognize the rust area, and the position information, rust grade, and size information of the rust area are obtained. Then a 100 W laser rust removal system is used to remove the identified rust, and the derusted workpiece is recognized and detected again. After applying the machine vision-assisted laser rust removal system, the contents of C and O elements on the surface of 16Mn fall below 5%. The laser intelligent rust removal assisted by machine vision can quickly and efficiently identify the rust on the surface of the workpiece. The visual algorithm and process database are used to quickly match the corresponding processing parameters, so as to improve the processing efficiency and reduce the labor cost.