摘要
针对柴油机的机体表面振动信号的非平稳、含噪声的复杂性,提出了一种提升小波去噪与局域波分析相结合的新方法,并用于机体表面振动信号的特征提取和状态识别.首先构造提升小波对信号进行自适应消噪处理,避免局域波分解过程中虚假模式分量的产生;然后将消噪信号进行局域波分解,通过局域波边际谱分析信号能量随瞬时频率的变化特征.柴油机缸套活塞间磨损故障的实测振动信号分析结果验证了应用该方法进行柴油机故障特征提取和状态识别的有效性.
In respect to the non-stationary and noise characteristics of the surface vibration signals meas-ured from the diesel engine,a novel method combining local wave analysis and lifting wavelet de-noising is proposed,and is used for feature extraction and state identification of diesel engine vibration signals.Firstly,the original data is preprocessed using the lifting wavelet transformation to remove abnormal in-terference of noise,and avoid the pseudo mode functions from local wave decomposition（LWD）.Sec-ondly,the intrinsic mode functions are obtained by using LWD,and the instantaneous frequency and energy distribution of signals can be extracted by local wave boundary-spectrum.The vibration signals of diesel engine piston-liner wear are analyzed.Results show that the method is feasible and effective in fea-ture extraction and state identification of diesel engine faults.
出处
《内燃机学报》
EI
CAS
CSCD
北大核心
2011年第4期321-326,共6页
Transactions of Csice
基金
国家自然科学基金资助项目(50805014)
中央高校基本科研业务费专项资金资助项目(2009JC14)
关键词
柴油机
局域波分析
提升小波变换
故障诊断
diesel engine
local wave analysis
lifting wavelet transform
fault diagnosis
