摘要
针对路面二阶有理函数功率谱密度参数识别问题,以二阶有理函数功率谱密度与国际标准化组织给出的幂函数功率谱密度数值差的均方值最小为优化目标,建立了路面二阶有理函数功率谱密度参数识别的优化计算模型。采用遗传算法,获得了A～D级路面二阶有理函数功率谱密度参数最优值。在此基础上,采用谐波叠加法构建了路面不平度模型,并利用自回归(AR)模型的功率谱密度估计方法对创建的路面进行了谱分析。结果表明,路面二阶有理函数功率谱密度与幂函数路面分级标准数值吻合程度很好,应用遗传算法能准确识别出路面二阶有理函数功率谱密度参数。
Aiming at the parameter identification problem of power spectral density（PSD） of pavement second-order rational function,an optimization calculation model was established,in which the minimum mean-square-error of second-order rational function PSD and power function PSD given by ISO was chosen as the optimization objective.The optimum parameters of A-to D-grade pavement second-order rational function PSD were obtained by the genetic algorithms.On this basis,a road roughness model was established based on the basic principles of harmonic superposition.Then the spectrum analysis of the established road roughness model was made using auto regressive（AR） model power spectrum density estimation method.Results indicated that the pavement second-order rational function PSD was well coincidental with standard road classification power function PSD given by ISO,and the parameters of pavement second-order rational function PSD could be accurately identified using the genetic algorithms.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2012年第8期128-133,共6页
Transactions of the Chinese Society of Agricultural Engineering
基金
山东省自然科学基金资助项目(ZR2009FM044)
青岛大学优秀研究生学位论文培育项目(YSPY2011005)
关键词
遗传算法
参数识别
功率谱密度
路面不平度
genetic algorithms
parameter identification
power spectral density
road roughness
