基于小波分析的车轮六分力信号的去噪研究

Study on Denoising of Six Axis Wheel Force Signal Based on Wavelet Analysis

介绍了利用小波分析去噪的原理,分析了小波变换模极大值法、小波系数尺度相关法和阈值法3种信号处理方法的特点,详述了利用阈值法处理信号时选择小波基、确定分解层、阈值处理和信号重构的方法。利用Matlab的小波分析工具箱对车轮纵向力信号进行去噪分析应用,结果表明:小波分析能很好的区分信号里的突变信号与多余的噪声,通过小波重构得到去噪后的车轮分向力突变的信号。本设计具有一定的应用价值。

The principle of denoising with wavelet analysis was introduced. The characteristics of three signal processing methods： wavelet transform method, wavelet coefficient scale correlation method and threshold method, were analyzed. The methods of selecting wavelet base, determining decomposition level, threshold processing and signal reconstruction during processing signal by threshold method were described. A denoising analysis on the wheel longitudinal force signal was carried out by using the wavelet analysis toolbox in Matlab. The results show that the sudden signal and excess noise can be effectively identified by wavelet analysis, and the sudden signal of wheel longitudinal force after denoising are obtained by wavelet reconstruction. The design has an application value.