机械加工表面粗糙度的图像检测方法

Image Detection Method of Machined Surface Roughness

以LabVIEW 7.1为开发平台,设计了一种用于机械加工表面粗糙度的图像检测方法.完成了测量方向的标定,获得了图像上灰度分布标准差最大的5个截面,通过巴特沃斯滤波,得到了与这5个截面对应的滤波前后的灰度信息.灰度变化反映了轮廓的高低起伏,故可求出类似于轮廓算术平均偏差Ra的参数Ra',并初步建立了Ra与Ra'之间的数学表达式.最后,利用ActiveX技术,实现LabVIEW与Excel之间的通信,将用于后续分析的信息自动导入Excel中,生成数据报告单.

This paper took LabVIEW7.1 as the development platform to design an image detection method applied to measure the machined surface roughness. We brought calibration of measuring direction into effect, and obtained five sections which had the highest standard deviation of gray variance in the image. Then we gained the five sections＇ corresponding gray information both before and after Butterworth filtering. Taking gray variation as profile fluctuation, we could get a parameter Ra＇similar to arithmetic mean deviation of profile Ra, and establish the preliminary, mathematical representation between Ra and Ra： At last, we achieved the communication between LabVIEW and Excel through ActiveX technology. So the information which would be analyzed later was automatically transmitted to Excel, with the generation of a data sheet.