基于DSP的磨削表面粗糙度在线检测系统开发

为了解决磨削工件在线粗糙度等级识别速度慢和准确性不高的问题,开发了基于DSP的工件表面粗糙度在线检测系统.该系统基于光散射原理,通过工业相机采集光散射图像,运用DSP芯片对采集到的图像进行图像预处理以及特征参数的提取;最后利用建立的多分类支持向量机模型,对不同表面粗糙度等级的图像进行分类.实验结果表明,在该硬件平台上整个识别过程耗时约0.5s,识别率可达96%以上,说明该系统可有效识别工件表面粗糙度等级,有效实现工件表面粗糙度的在线检测.

Development of the Online Measuring System of Grinding Surface Roughness Based on DSP

In order to solve the problems about slow speed and low accuracy on the online roughness recognition of the grinding workpiece, an online measurement system for surface roughness was developed based on DSP. In this system, the surface scattered images based on the light scattering principle were captured by an industrial camera, then these images were preprocessed and their feature parameters were extracted by the DSP chip. Finally, these images with different surface roughness were classified by the multi-class support vector machine model. Experimental results show that it takes about 0.5 s for the entire identification process and the recognition rate can be up to 96% or more on this hardware platform, so this designed system can effectively identify the level of the surface roughness and realize the online testing of surface roughness.