基于小波去噪的快速定点ICA及其在振源识别中的应用 |
| |
引用本文: | 武志勇,陈茜.基于小波去噪的快速定点ICA及其在振源识别中的应用[J].顺德职业技术学院学报,2006,4(1):6-8,12. |
| |
作者姓名: | 武志勇 陈茜 |
| |
作者单位: | 1. 顺德职业技术学院,广东,顺德,528333 2. 五邑大学信息学院,广东,江门,529020 |
| |
摘 要: | 在多源激励情况下,从传感器阵列输出的高维响应中分离、识别不同振源的性质,对于大型结构振动分析以及对其状态监测与健康评价有着重要的意义.本文结合大型结构振动的性质,介绍了小波阈值去噪原理,使用其改进的快速定点算法实现了多源激励情况下振源信息分离的方法.文中通过实例给出了这种方法的应用效果.
|
关 键 词: | 振动测试 小波去噪 GMICA算法 独立分量分析 |
文章编号: | 1672-6138(2006)01-0006-03 |
收稿时间: | 2006-03-10 |
修稿时间: | 2006-03-10 |
Fast ICA Algorithm and Its Application to Recognition of Vibration Sources Based on Wavelet De-noising |
| |
Authors: | Wu Zhi-yong Chen Xi |
| |
Institution: | 1. Shunde Polytecnic Shunde GuangDong 528333, China; 2. Information institute of Wuyi University, Jiangmen Guangdong 529020,China |
| |
Abstract: | To separate and recognize characters under the excitation of multiple sources is a useful technique for infrastructure vibration analysis. This paper discusses an excitation sources separating approach using improved fast fixed point ICA and wavelet de-noising in consideration of peculiarities from the vibration of large scale structures. In additions, its merits are illustrated by real world vibration date. |
| |
Keywords: | vibration test wavelet De-noising GMICA algorithm independent components analyses |
本文献已被 CNKI 维普 万方数据 等数据库收录! |