An improved rough surface modeling method based on linear transformation technique

作者：Liao, Dongri; Shao, Wen^*; Tang, Jinyuan; Li, Jianping

来源：Tribology International, 2018, 119: 786-794.

DOI：10.1016/j.triboint.2017.12.008

• Linear transformation
• Rough surface
• Modeling
• Time series method

An effective rough surface model is the foundation for the evaluation of the contact, lubrication, friction and wear behaviors of engineering assemblies. This study first presented an investigation of the time series method, linear transformation method and Johnson transformation system. Then, an improved rough surface modeling method was proposed. The solving of the autocorrelation coefficient matrix was transformed to a nonlinear least squares problem and the analytical gradient formula was derived. The fast Fourier transform (FPI) method was further employed to improve the computational efficiency. Using this approach, rough surfaces with different autocorrelation ACF) and statistical parameters were generated and then compared with the prescribed surfaces. It was found that the ACF, areal autocorrelation AACF) and statistical parameters of the simulated surfaces were consistent with those of the prescribed surfaces. Moreover, an extremely good agreement was also found between the measured and generated grinding surfaces in terms of ACF, AACF and statistical parameters, which further proved the validity of the proposed method at large autocorrelation length. Therefore, the technique developed in this study may serve as a novel approach to generate rough surfaces with high efficiency and accuracy.

• 出版日期2018-3
• 单位高性能复杂制造国家重点实验室; 中南大学