The non-Gaussian rough surface simulation method with desired spatial distribution and height distribution is generally used to analyse the contact characteristics of rough surfaces under different contact conditions. Conventional surface simulation methods have disadvantages in terms of their range, accuracy, and stability. In this study, the analytical function method is enhanced to generate non-Gaussian random number matrices. The enhanced method was combined with the spectral representation method and an iterative algorithm to accurately and stably generate rough surfaces characterized by extensive skewness, kurtosis and autocorrelation lengths. The skewness and kurtosis range of the generated rough surface includes skewness and kurtosis of most engineering surfaces, such as worn surfaces and various machined surface and irregular engineering surfaces. A rough surface is easily generated ≤ 10 s.

中文翻译：

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使用解析函数和带有迭代算法的光谱表示方法生成非高斯粗糙表面


通常采用具有所需空间分布和高度分布的非高斯粗糙表面模拟方法来分析不同接触条件下粗糙表面的接触特性。传统的表面仿真方法在范围、精度和稳定性方面存在缺点。在本研究中，增强了解析函数方法以生成非高斯随机数矩阵。增强方法与光谱表示方法和迭代算法相结合，准确、稳定地生成具有广泛偏度、峰度和自相关长度特征的粗糙表面。生成的粗糙表面的偏斜度和峰度范围包括大多数工程表面的偏度和峰度，例如磨损表面和各种机加工表面和不规则工程表面。10 秒≤很容易产生粗糙的表面。