第44卷第4期2023年4月激光杂志LASERJOURNALVol.44,No.4April,2023http∶//www.laserjournal.cn收稿日期:2022-08-23基金项目:河北省重点研发计划项目(No.22375801D)作者简介:王艳贞(1982-),女,硕士,主要研究方向:图形图像三维虚拟仿真。三维成像技术的光学元件表面粗糙度智能测量方法王艳贞,王晓芬,韩立华石家庄铁道大学,石家庄050000摘要:光学元件在多个领域起着至关重要的作用,其应用性能的优劣主要由表面粗糙度决定,对此,提出三维成像技术的光学元件表面粗糙度智能测量方法。采集光学元件表面图像,并进行预处理,然后采用重构算法获取到光学元件表面三维图像,并使用最小二乘中线提取元件表面三维形貌的中面,最后在表面三维形貌中面计算出三维粗糙度评价参数,实现光学元件表面粗糙度智能测量。实验数据显示:设计方法测量的表面粗糙度因子平均误差最小值达到了0.5%,测量精度高达100%,证明本方法的光学元件表面粗糙度测量性能较佳。关键词:光学元件;智能测量;三维成像技术;表面粗糙度;三维评定;多层聚焦中图分类号:TN249文献标识码:Adoi:10.14016/j.cnki.jgzz.2023.04.229Intelligentmeasurementmethodofopticalelementsurfaceroughnessfor3dimagingtechnologyWANGYanzhen,WANGXiaofen,HANLihuaShijiazhuangTiedaoUniversity,Shijiazhuang050000,ChinaAbstract:Opticalelementsplayanimportantroleinmanyfields,andtheirapplicationperformanceismainlyde-terminedbysurfaceroughness.Therefore,anintelligentmeasurementmethodofopticalelementsurfaceroughnessbasedon3Dimagingtechnologyisproposed.Theopticalelementsurfaceimageiscollectedandpretreated,andthenthereconstructionalgorithmisusedtoobtainthethree-dimensionalimageoftheopticalelementsurface,andthemid-dlesurfaceofthethree-dimensionalsurfacetopographyoftheelementsurfaceisextractedusingtheleastsquarecen-terline.Finally,thethree-dimensionalroughnessevaluationparametersarecalculatedonthemiddlesurfaceofthethree-dimensionalsurfacetopographytoachievetheintelligentmeasurementoftheopticalelementsurfaceroughness.Theexperimentaldatashowthattheminimumaverageerrorofthesurfaceroughnessfactormeasuredbythedesignmethodreaches0.5%,andthemeasurementaccuracyreaches100%,whichprovesthattheopticalelementsurfaceroughnessmeasurementperformanceofthem...
