Generation of non-Gaussian rough surfaces based on fractal theory and genetic algorithm

Haibo Zhang, Shengli Liu, Wenzhong Wang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

A new method that combines the fractal theory, Weibull distribution and genetic algorithm (GA) is proposed in the present study to generate engineering non-Gaussian rough surfaces (NGS) with specified kurtosis and skewness. By adjusting the GA parameters, the generated surfaces cover the NGS corresponding to various machining methods used in engineering. Good agreement was found when compared with real engineering rough surfaces measured experimentally. Compared with the methods in the literature, the advantages of the present method include generating rough surfaces with a much wider range of specified kurtosis and skewness, and with scale-independent and more realistic topography.

Original languageEnglish
Article number110530
JournalTribology International
Volume205
DOIs
Publication statusPublished - May 2025

Keywords

  • Fractal theory
  • Genetic algorithm
  • Non-Gaussian rough surface
  • Weibull distribution

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Zhang, H., Liu, S., & Wang, W. (2025). Generation of non-Gaussian rough surfaces based on fractal theory and genetic algorithm. Tribology International, 205, Article 110530. https://doi.org/10.1016/j.triboint.2025.110530