In this paper, topography characteristics are statistically analyzed based on a large number of field measured data to investigate the roughness failure on textured work rolls and the evolution on steel strips during cold rolling and temper rolling. It is revealed that the height distribution in the surface profile of steel strips is barely influenced by the skewed height distribution in the surface profile of work rolls. The roughness of steel strips is efficiently improved by the last stand of cold rolling, while the peak count is mainly increased by the temper rolling. A prediction model of surface roughness for temper rolled strips is established afterwards. This model indicates that the most important factor influencing the roughness of temper rolled strips is the product of reduction and tension ratio. The influence degree of the rolling process parameters is presented, which is helpful to regulate surface roughness of the steel strips by setting and adjusting these parameters during the industrial production process.
The surface topography of temper rolled strip consists of a range of spatial wavelengths with approximate normal distribution in height. Gaussian filtering methods can be applied in measuring and characterizing the topography of temper rolled strip. In this study, three Gaussian filtering algorithms, namely convolution algorithm, fast Fourier transform algorithm and fast recursive algorithm, are compared, in order to find out the most suitable one for the topography of temper rolled strip. A similar profile extension method based on the distribution of the topography of strip is proposed to eliminate the edge effect. The results show that the convolution algorithm is obviously beneficial for the computational efficiency. It is also found that the similar profile extension method can effectively eliminate the edge effect and improve the reliability of edge data. The Gaussian convolution algorithm, combined with the similar profile extension method, is able to effectively assess the surface topography of temper rolled strip.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.