首页 | 本学科首页   官方微博 | 高级检索  
     

刮板细度计非接触测量数据处理研究
引用本文:金挺,陈挺.刮板细度计非接触测量数据处理研究[J].计测技术,2021,41(1):27-30.
作者姓名:金挺  陈挺
作者单位:浙江省计量科学研究院,浙江杭州310018
基金项目:国家重点研发计划(2017YFF0206305);浙江省市场监督管理局科研项目(20150216,20180104)。
摘    要:对基于光谱共焦技术搭建的刮板细度计斜槽面深度测量装置的非接触测量数据进行处理算法研究.引入高斯滤波对整段测量数据进行滤波分析,再分左上平面、右上平面、斜槽底面三段进行高斯滤波,分离三个测量面的表面粗糙度信号及波纹度信号,解算出粗糙度值.对于高斯滤波中线,利用最小二乘法进行拟合,结果表明左右上平面的直线倾斜度一致,可拟合...

关 键 词:刮板细度计  光谱共焦  非接触测量  高斯滤波  最小二乘法

The process of the Measurement Data of Non-contact Grind-Fineness-Gage Measuring-Device
JIN Ting,CHEN Ting.The process of the Measurement Data of Non-contact Grind-Fineness-Gage Measuring-Device[J].Metrology & Measurement Technology,2021,41(1):27-30.
Authors:JIN Ting  CHEN Ting
Affiliation:(Zhejiang Institute of Metrology,Hangzhou 310018,China)
Abstract:The processing algorithm of the non-contact measurement data of the fineness of grind gage based on the spectral confocal technology is studied.The Gaussian filter is used to filter and analyze the whole measurement data,and then the Gaussian filtering is carried out in three sections of upper left plane,upper right plane and bottom surface of the chute.The surface roughness signal and waviness signal of the three measuring surfaces are separated and the roughness value is calculated.The least square method is used for Gaussian filter median line.The filtering results show that the inclination of the straight lines on the left and right upper planes are consistent and can be fitted into one straight line.Taking the straight line fitted as the datum line,the depth from the scanning point of the chute surface to the datum line is obtained,and the indicating error of the nominal value of the chute surface depth of 90μm is(0.27~1.97)μm.Compared with the data obtained from the contact measurement of inductance micrometer,the results show that the data processing method for noncontact measurement is feasible and the measurement results are accurate and reliable.
Keywords:fineness of grind gage  spectral confocal  non-contact measurement  Gaussian filtering  least square method
本文献已被 维普 万方数据 等数据库收录!
点击此处可从《计测技术》浏览原始摘要信息
点击此处可从《计测技术》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号