摘要
阐述了几种传统小波去噪原理及其优缺点,在此基础上提出了一种基于能量元和Neyman-Pearson准则的小波阈值去噪算法,并将其用于路面不平度数据的降噪分析。仿真结果表明,该算法不仅能最大限度地保留路面不平度信号的趋势部分,而且能有效降噪。
Several principles and the advantages and faults of the traditional wavelet de-noising are both described,then a de-noise method base on energy-member and Neyman-Pearson Criteria is proposed and used for de-noising in the road roughness data.Numerical simulations show that the algorithm can not only maximize the retention of road roughness trends,but also is effective and excellent in de-noising.
出处
《机械设计与制造》
北大核心
2011年第4期65-67,共3页
Machinery Design & Manufacture
基金
国家高技术研究发展计划(863计划)项目(2006AA110116-04)
