航空发动机气路静电信号联合降噪方法
A Combined Denoising Method for Electrostatic Signals in the Aero-engine Gas Path
刘岩 1刘珍珍 2白芳 3郭泽中 1左洪福1
作者信息
- 1. 南京航空航天大学民航学院,南京 211106
- 2. 安徽工业大学机械工程学院,马鞍山 243032
- 3. 南京电子工程研究所,南京 210023
- 折叠
摘要
针对强背景噪声下航空发动机气路静电信号降噪问题,提出一种基于本征模态函数(Intrinsic modal function,IMF)自适应滤波联合小波阈值的静电信号降噪方法.首先,通过互补集合经验模态分解(Complementary ensemble empirical mode decomposition,CEEMD)方法对原始静电信号进行分解,得到若干平稳IMF;然后,构建最优重构自适应低通滤波算法筛选以有用信号为主的IMF分量;再对以噪声为主的IMF分量通过小波阈值算法进行降噪处理;最后,将上述信号重构,得到降噪后的静电信号.进行了仿真和实测信号验证并与传统方法对比,结果表明,该方法对发动机气路静电信号降噪效果良好,在微弱故障信号提取方面更具优越性.
Abstract
Aiming at the problem of noise reduction of electrostatic signals in the aero-engine gas-path under strong background noise,a noise reduction method based on intrinsic modal function(IMF)adaptive filtering combined with wavelet thresholding is proposed.Firstly,the original electrostatic signal is decomposed by the complementary ensemble empirical mode decomposition(CEEMD)method to obtain several smooth IMFs.Secondly,the optimal reconstruction adaptive low-pass filtering algorithm is constructed to filter the signal-dominated IMFs.Thirdly,the noise-dominated IMF components are noise-reduced and reconstructed with the signal-dominated IMFs by the wavelet thresholding method,then the noise-reduced electrostatic signal is obtained.The simulated and measured signals are used to verify the proposed method and compare it with other noise reduction methods,and the results show that the method is effective in noise reduction of engine gas-path electrostatic signals and is superior in extracting weak fault signals.
关键词
自适应降噪/互补集合经验模态分解/小波阈值/静电监测/航空发动机Key words
adaptive signal denoising/complementary ensemble empirical mode decomposition(CEEMD)/wavelet threshold method/electrostatic monitoring/aero-engine引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据