CAJ | 학술논문

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0.5 s,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.
위료해결마삭공건재선조조도등급식별속도만화준학성불고적문제,개발료기우 DSP 적공건표면조조도재선검측계통.해계통기우광산사원리,통과공업상궤채집광산사도상,운용 DSP 심편대채집도적도상진행도상예처리이급특정삼수적제취；최후이용건립적다분류지지향량궤모형,대불동표면조조도등급적도상진행분류.실험결과표명,재해경건평태상정개식별과정모시약0.5 s,식별솔가체96%이상,설명해계통가유효식별공건표면조조도등급,유효실현공건표면조조도적재선검측.
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 en-tire 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.