Objective To study the influence of different autocorrelation lengths on the surface characterization parameters after reconstruction during computer simulation. The method adopts the new FFT method, keeps the specific parameters (height root mean square, skewness, peak value) unchanged, and performs a total of 16 different combinations of different autocorrelation lengths (3, 10, 30, 100) in two directions. The computer simulation experiment of sub-three-dimensional rough surface topography, and from the angle of the combination of autocorrelation length in different directions, the influence of the parameters with higher correlation with topography features is analyzed. Results The arithmetic average peak curvature, peak density, and root mean square slope are generally negatively correlated with the autocorrelation length in the two directions, and the fastest descending autocorrelation length is positively correlated with the autocorrelation length in the two directions, and the texture height and width The ratio is related to whether the autocorrelation lengths in the two directions are close. The peak density and the fastest descending autocorrelation length are all sensitive to the smaller autocorrelation length of different autocorrelation lengths, while the response to the change of the larger autocorrelation length is more sensitive. Small, the arithmetic mean peak curvature and root mean square slope show the same higher sensitivity. Conclusion There is no relationship between the height distribution parameter and the autocorrelation length in the surface characterization parameters, while the structure ratio parameter has a significant correlation with the autocorrelation length.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)