Assessment mean lines of surface texture based on ISO5436-2

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 R_a, R_q, R_p, R_v, R_sk, R_ku 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 R_sk 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 R_sk with relative errors of 3.55% and -7.45% and R_p 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 R_a, R_q are relatively smaller, but the others are bigger. After excluding the jumping bump, the deviation values of R_a, R_q are still relatively smaller, those of R_sk and R_p are minishied from big to small, but those of R_ku, R_p 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 R_a, R_q can be assessed by the least square method which is simple and easy to be realized.