基于奇异值分解和经验模态分解的航空发动机健康信号降噪

doi:10.7964/jdxbgxb201303034

吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (03): 764-770.doi: 10.7964/jdxbgxb201303034

基于奇异值分解和经验模态分解的航空发动机健康信号降噪

雷达, 钟诗胜

哈尔滨工业大学机电工程学院,哈尔滨 150001

收稿日期:2012-03-30 出版日期:2013-05-01 发布日期:2013-05-01
通讯作者: 钟诗胜(1964-),男,教授,博士生导师.研究方向:复杂装备健康管理.E-mail:zhongss@hit.edu.cn E-mail:zhongss@hit.edu.cn
作者简介:雷达(1984-),男,博士研究生.研究方向:装备健康状态监控与预测.E-mail:raydar@163.com
基金资助:
"863"国家高技术研究发展计划重点项目(2012AA040911-1);国家自然科学基金项目(60939003);中国民航总局科技项目(MHRD201052).

Aircraft engine health signal denoising based on singular value decomposition and empirical mode decomposition methods

LEI Da, ZHONG Shi-sheng

School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China

Received:2012-03-30 Online:2013-05-01 Published:2013-05-01

摘要/Abstract

摘要： 提出了一种基于奇异值分解(Singular value decomposition, SVD)和经验模态分解(Empirical mode decomposition, EMD)的信号降噪方法.首先采用EMD方法对原始信号进行分解并提取出信号趋势分量.然后对信号剩余部分采用SVD方法降噪,并根据奇异值差分谱方法自适应选择奇异值进行信号重构.最后将重构后的信号与趋势分量叠加得到最终的降噪信号.采用该方法对模拟信号和实际航空发动机健康信号进行了降噪试验,结果表明:该方法能够准确地选择用于重构信号的奇异值,并能够有效地去除信号噪声.

关键词: 信息处理技术, 信号降噪, 奇异值分解, 经验模态分解, 航空发动机

Abstract: Singular Value Decomposition (SVD) is a widely used nonlinear signal denoising approach. Its denoising effect is depending on the selection of singular values for the signal reconstitution. The singular value difference spectrum of singular value can be used to select the expected singular values adaptively. However, sometimes when dealing with signals with strong trend, such as aircraft engine health signals, it may hardly choose the right singular values and fail to restore the desired signals To solve such problem, a signal denoising approach based on Empirical Mode Decomposition (EMD) and SVD is proced. First, the original signal is decomposed by EMD and the trend component is extracted from the original signal. Then, SVD is used to denoise the detrended signal, and the difference spectrum of singular value is used to select the singular values adaptively. After denoising, the detrended part is added to the trend part to get the final signal. Results of Both simulation and real aircraft engine health signal experiment demonstrate that the proposed approach can precisely select the singular values for signal reconstitution and effectively reduce the noise.

Key words: information processing, signal denoising, singular value decomposition(SVD), empirical mode decomposition(EMD), aircraft engine

中图分类号:

TN911.7

雷达, 钟诗胜. 基于奇异值分解和经验模态分解的航空发动机健康信号降噪[J]. 吉林大学学报(工学版), 2013, 43(03): 764-770.

LEI Da, ZHONG Shi-sheng. Aircraft engine health signal denoising based on singular value decomposition and empirical mode decomposition methods[J]. 吉林大学学报(工学版), 2013, 43(03): 764-770.

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基于奇异值分解和经验模态分解的航空发动机健康信号降噪

Aircraft engine health signal denoising based on singular value decomposition and empirical mode decomposition methods

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