摘要
根据路面不平度的现有分级标准,采用傅里叶逆变换的方法模拟8个等级路面不平度高程数据,计算路面不平度的分形参数,提出路面不平度的分形分级参数。计算分析结果表明,傅里叶逆变换方法模拟的各级路面分形维数均在1.60左右,差别很小,表现出明显的自相似性;路面不平度指数结合了路面不平度的传统的统计特征参数与分形维数,因而更适合路面不平度的分级;路面不平度指数随功率谱密度的增大而增大,且由高级到低级呈明显增大趋势,路面不平度等级越差,路面不平度指数越大。
The eight-grade road surface data were simulated by inverse Fourier transform, according to road surface roughness grade standard. Its fractal parameters were calculated and the fractal parameter for the grade of road surface roughness was proposed. The result shows that the simulating roads display obvious similarity. Its fractal dimension was approximately 1.60, which had little difference of grade. The road surface roughness index unified the traditional statistical parameter and the fractal dimension, which was more suitable for the grade of the road surface. The road surface roughness index increases with the power spectral density. In other words, the lower the road surface roughness index is, the worse the road surface grade becomes.
出处
《交通与计算机》
2008年第6期158-161,共4页
Computer and Communications
关键词
路面不平度
分级
分形参数
road surface roughness
grade
fractal parameters
