基于小波包分析的道路信号加速度特征谱提取

道路信号是一个复杂的含有多种成分的时域波形, 具有非平稳性, 同时信号中还存在各种干扰和噪声. 应用小波包的分解与重构算法, 将由加速度传感器测得的离散时域信号的频带进行多层次划分, 并根据被分析信号的特征, 选择相应的频带, 使之与信号频谱相匹配, 从而提高了时-频分辨率, 最后提取出加速度信号的特征谱. 实验结果表明, 小波包分析可以有效地用于分析处理道路信号.

Extracting Eigenvalue and Eigenvector of the Road Signals Based on Wavelet Packet's Analysis

The signals collected directly from the road are very complicated in the time domain,which have nonstationarity and contain many kinds of components,and there are various disturbances and noises in them.The decomposing and reconfiguring algorithm of wavelet packet is studied.It can divide the band of scattering signals from the acceleration sensor with multiple echelons,according to the characteristic of the analyzed signal,choose the correspond band,and make the signal frequency spectrum appearance match,then the resolution factor of time-frequency is improved.Finally,characteristic spectrum of the acceleration signals is extracted.The experiment results show that wavelet analysis can be used effectively to analyze and process road signals.