南昌工程学院学报2017，Vol.36Issue(1)：68-72,5.
小波分析在AR模型重构路面不平度中的应用
Application of wavelet analysis method in reconstruction of road roughness in AR model
摘要
Abstract
Aiming at the problem that the error in the low frequency band was large when reconstructing the road roughness in AR model,the wavelet analysis method was proposed to improve the reconstructed random road for its time-frequency characteristic.Firstly,the power spectrum of the grade road was used to reconstruct the C-level random road in the AR model.The random road was then decomposed by the wavelet decomposition method and the wavelet packet decomposition method.The amplitude of components at each frequency band was adjusted to approach the given power spectrum under the principle that the signal energy was proportional to the square of the signal amplitude.Finally,a random road was reconstructed by those adjusted components and compared with the standard road in time and frequency domain.The results show that both methods can improve the relative error between the reconstructed road roughness PSD and standard one.Furthermore,wavelet packet decomposition method has more advantages in fitting the high frequency components.关键词
路面不平度/AR模型/小波分析/路面功率谱Key words
road roughness/AR model/wavelet analysis/road power spectrum分类
交通工程引用本文复制引用
谢明祥..小波分析在AR模型重构路面不平度中的应用[J].南昌工程学院学报,2017,36(1):68-72,5.基金项目
江西省教育厅科技项目(GJJ151108) （GJJ151108）
南昌工程学院青年基金科技项目(2014KJ013) （2014KJ013）
