摘要
激光经过被测表面反射和散射后,通过自由空间传播至观察面上形成散斑图像,其统计分布依赖于被测表面的微观形貌。分析此散斑图像的二阶统计特性,导出了强度变化的相关函数和表面粗糙度参数之间的关系。以表面粗糙平均值Ra分别为0.1靘, 0.2靘, 0.4靘和0.8靘的平磨标准金属样块形成的散斑图像为例,根据强度变化相关函数的离散化定义,计算得到该相关函数值。结果表明,表面越粗糙,散斑越分散,强度变化的相关函数波动越大。因此,该参数可以反映不同的粗糙面,用其作为表征表面粗糙度的特征参数,扩大了测量范围。该方法实验系统简单,对于实际测量环境要求不高,对震动不是非常敏感,适于在线测量。
Speckle images are produced by the reflected and scattered light beams from rough surface through free-space to observing plane when laser illuminates the object surface. Statistical distribution of speckles depends on the microscopic structure of the rough surface. The relation between the correlation function of intensity variation and surface roughness parameter is derived through analyzing the second-order statistical properties of the speckle image. Taking the speckle images formed by flat-ground standard samples with Ra (the average value of surface roughness) as 0.1micron, 0.2micron, 0.4micron and 0.8micron, respectively, for examples, the correlation function is obtained according to the calculation for discretization definition of its intensity variations. It is shown that the rougher the surface becomes, the more the speckle disperses, the larger the fluctuation of correlation function intensity presents. So, the parameter can be used to character the surface roughness and describe the surface roughness in large range. The experimental set-up of the method is very simple, fast, and not sensitive to change of circumstance and vibration. Hence, it has great potential for application to in-process measurement.
出处
《光电工程》
CAS
CSCD
北大核心
2004年第7期50-53,共4页
Opto-Electronic Engineering
关键词
表面粗糙度测量
散斑图像
强度相关函数
Surface roughness measurement
Speckle images
Intensity correlation function
