为了探讨激光微造型表面仿生非光滑效应中粗糙度提高的工艺,运用SEM扫描电镜和图像处理技术提取荷叶表面微纳米形貌特征,在犁铧钢(18CrMnTi)表面进行激光微造型表面仿生正交试验研究.研究表明,图像处理中Sobel边缘算法有效地提取了SEM图片表面微纳米形貌层次特征,图像阈值取255时,提取表面形貌特征最多,犁铧钢仿生表面基本上再现了荷叶表面形貌:激光表面微造型极显著因素的主次关系是阈值＞打标次数＞电流强度,表面仿生最优值处的微造型粗糙度参数,即表面轮廓算术平均偏差(Ra)、微观不平度十点高度(Rz)和最大轮廓高度(Ry)提高的倍数分别为86.11、232.29和116.06.研究结果为激光微造型表面仿生多层次提取表面形貌信息和提高表面粗糙度工艺提供参考.%In order to explore surface roughness technology in non-smooth bionic affection by laser micro-texturing, the orthogonal experiment was made in the plowshare (18CrMnTi) steel bionic surface, based on scan electron microscopy (SEM) photos and the technique of image processing to extract micro-nano-morphology information form lotus leaf surface. Results showed that in the processing of image Sobel edge operator was the most effective method for extracting layers information of SEM micro-nano-morphology photos. The extracted morphology information was up to maximum value at the point of threshold value 255, and surface morphology of lotus leaf was textured in the plowshare surface. The relationship of significant experimental factors was, threshold value > number of marking > current intensity. The optimal values of roughness parameters, I.e. Ra, Rz and Ry increased by 86.11, 232.29 and 116.06 times respectively. This research has significance in extracting the surface information of layers morphology and enhancing the surface roughness by laser micro-texturing bionic surface.
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