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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.
Aiming at the non-stationary and noise-containing complexity of the vibration signal on the surface of a diesel engine, a new method combining lifting wavelet denoising and local wave analysis is proposed and used to extract the feature and identify the state of the surface vibration signal. The lifting wavelet is constructed to adaptively denoise the signal and avoid the generation of false mode components in the process of local wave decomposition. Then, the noise signal is decomposed by the local wave, and the signal energy is analyzed with the change of instantaneous frequency The results of the measured vibration signal analysis of the diesel engine cylinder liner wear testified the effectiveness of the proposed method for diesel engine fault feature extraction and condition identification.