基于小波的浮筏振动信号特征提取方法  

Method for Extracting Features from Floating Raft Vibration Signals Based on Wavelet

作　　者：李萍[1] 王春麟[1] 

机构地区：[1]武汉理工大学机电工程学院,湖北武汉430070

出　　处：《武汉理工大学学报（信息与管理工程版）》2010年第5期742-745,共4页Journal of Wuhan University of Technology：Information & Management Engineering

基　　金：国家自然科学基金资助项目(50675163)

摘　　要：针对浮筏振动信号受到强烈的随机噪声干扰,给它的特征提取带来很大困难的问题,对浮筏振动信号特征进行小波降噪。通过仿真实验,对比分析了几种不同小波函数和阈值函数对浮筏振动信号降噪性能的影响。分析结果表明,在选取的小波函数和阈值函数中高阶db小波以及最优预测变量阈值函数有利于减小小波重构信号与真实信号的误差,降噪效果明显。通过振动测试验证了其降噪效果。Due to strong random noise in floating raft vibration signals,it is very difficult to extract their features,so wavelet denoising method based on vibration signal characteristics was applied.The noise control effects of several different wavelet functions and threshold functions were investigated by the simulation experiment.Experimental results showed that higher-order Daubechies wavelet and heursure thresholding could reduce the error between the wavelet reconstruction signal and the true signal.And a good performance was achieved for the noise reduction.Finally the effectiveness was validated through the experiment.

关 键 词：浮筏振动信号 小波降噪 小波函数 阈值函数 

分 类 号：TN911.72[电子电信—通信与信息系统]