Assessment mean lines of surface texture based on ISO5436-2

Changcai Cui, Xiang Qian Jiang, Xiao Gai Li, Xiao Jun Liu

Research output: Contribution to journalArticle

Abstract

In order to evaluate the performance of software and instruments, the assessment mean lines of roughness profiles are researched by means of Gaussian filtration, least square mean lines and the least square conic fitting on the basis of the software standard ISO 5436-2. And by simulating manufacturing process data, measuring EDM surface data and honing surface data, the typical roughness profile parameters Ra, Rq, Rp, Rv, Rsk, Rku defined in ISO 4287 are assessed and their deviation values from standard results are analyzed. Experimental results indicate that for the simulated process data, the results given by three kinds of mean lines are all better than those of the original ones, except the deviation value of Rsk is relatively bigger by 50% or so than that given by the least square method. For the EDM surface data, the deviation values given by the Gaussian filtration are smaller and those given by other two least square mean lines are a little bigger. The relatively bigger ones are Rsk with relative errors of 3.55% and -7.45% and Rp with relative errors of -3.45% and 3.95% respectively. For the honing surface data, the parameter deviation values are all bigger computed under three mean lines because of the jumping bump, and the deviation values of parameters Ra, Rq are relatively smaller, but the others are bigger. After excluding the jumping bump, the deviation values of Ra, Rq are still relatively smaller, those of Rsk and Rp are minishied from big to small, but those of Rku, Rp are still 40% or so. It can be concluded that the roughness parameters almost have no distinct difference based on the three mean lines for the profiles without jumping bump. Therefore, for the common precision profile without distinct periodical waveness components and bigger jumping bumps, the typical roughness parameters Ra, Rq can be assessed by the least square method which is simple and easy to be realized.

Original languageEnglish
Pages (from-to)1063-1071
Number of pages9
JournalGuangxue Jingmi Gongcheng/Optics and Precision Engineering
Volume17
Issue number5
Publication statusPublished - 1 May 2009

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textures
Textures
Surface roughness
Honing
deviation
honing
roughness
least squares method
profiles
computer programs
manufacturing

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Cui, Changcai ; Jiang, Xiang Qian ; Li, Xiao Gai ; Liu, Xiao Jun. / Assessment mean lines of surface texture based on ISO5436-2. In: Guangxue Jingmi Gongcheng/Optics and Precision Engineering. 2009 ; Vol. 17, No. 5. pp. 1063-1071.
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abstract = "In order to evaluate the performance of software and instruments, the assessment mean lines of roughness profiles are researched by means of Gaussian filtration, least square mean lines and the least square conic fitting on the basis of the software standard ISO 5436-2. And by simulating manufacturing process data, measuring EDM surface data and honing surface data, the typical roughness profile parameters Ra, Rq, Rp, Rv, Rsk, Rku defined in ISO 4287 are assessed and their deviation values from standard results are analyzed. Experimental results indicate that for the simulated process data, the results given by three kinds of mean lines are all better than those of the original ones, except the deviation value of Rsk is relatively bigger by 50{\%} or so than that given by the least square method. For the EDM surface data, the deviation values given by the Gaussian filtration are smaller and those given by other two least square mean lines are a little bigger. The relatively bigger ones are Rsk with relative errors of 3.55{\%} and -7.45{\%} and Rp with relative errors of -3.45{\%} and 3.95{\%} respectively. For the honing surface data, the parameter deviation values are all bigger computed under three mean lines because of the jumping bump, and the deviation values of parameters Ra, Rq are relatively smaller, but the others are bigger. After excluding the jumping bump, the deviation values of Ra, Rq are still relatively smaller, those of Rsk and Rp are minishied from big to small, but those of Rku, Rp are still 40{\%} or so. It can be concluded that the roughness parameters almost have no distinct difference based on the three mean lines for the profiles without jumping bump. Therefore, for the common precision profile without distinct periodical waveness components and bigger jumping bumps, the typical roughness parameters Ra, Rq can be assessed by the least square method which is simple and easy to be realized.",
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Assessment mean lines of surface texture based on ISO5436-2. / Cui, Changcai; Jiang, Xiang Qian; Li, Xiao Gai; Liu, Xiao Jun.

In: Guangxue Jingmi Gongcheng/Optics and Precision Engineering, Vol. 17, No. 5, 01.05.2009, p. 1063-1071.

Research output: Contribution to journalArticle

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