基于激光散斑分形维数的表面粗糙度测量方法

Surface Roughness Measurement Based on Fractal Dimension of Laser Speckle

采用激光照射粗糙工件表面形成散斑图像,通过自相关函数分析散斑图像的二阶统计特性,使用分形算法提取散斑图像自相关函数矩阵的参数,建立分形维数与表面粗糙度对应的样本集合。用最小二乘法多项式拟合该样本集合,得到散斑图像与表面粗糙度值间的多项式关系。实验结果表明,基于激光散斑分形维数的表面粗糙度测量方法是可行的且适用于在线高精度粗糙度检测,在检测时间上从数十秒级提高到秒级,检测精度达到微米级。

The speckle images of rough surface formed by laser irradiation of workpiece are analyzed using an autocorrelation function to obtain two- order statistical properties. Some parameters of the autocorrelation function are extracted from the speckle images using a fractal algorithm, and a sample set between the fractal dimension and the surface roughness is established and fitted by the least squares polynomial method. The experimental results show that the proposed surface roughness measurement method based on the fractal dimension of laser speckle is feasible and suitable for online high precision roughness detection. The detection time is shortened from tens of seconds to seconds and the detection accuracy reaches to micrometer scale.