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1.
基于EMD和HT的旋转机械振动信号时频分析   总被引:26,自引:9,他引:17  
把一列时间序列数据通过经验模态分解(Empirical Mode Decomposition,简称EMD)成本征模函数组(Intrinsic Mode Function.简称IMF).然后经希尔伯特变换(Hilbert Transformation,简称HT)获得频谱的信号时频分析新方法引入到旋转机械振动信号处理领域。介绍了该方法的理论和算法。首先.采用调频调幅仿真信号对该方法进行仿真验证;其次.把一实测的旋转机械油膜涡动故障振动信号进行了基于EMD和HT的时频分析。仿真和实测信号的分析结果说明.用基于EMD和HT方法对旋转机械的振动信号进行时频分析是有效的。  相似文献
2.
Hilbert-Huang变换的端点效应表现在两个方面,对信号进行经验模态分解(Empirical mode decomposition, EMD)和对各个内禀模态函数(Intrinsic mode function,IMF)进行Hilbert变换时都会产生端点效应。为了克服 Hilbert-Huang变换中的端点效应,采用支持矢量回归机对信号延拓后再进行经验模态分解,该方法可以有效地克服EMD方法的端点效应问题,得到具有物理意义的内禀模态函数;然后再次采用支持矢量回归机对IMF分量进行延拓后进行Hilbert变换,可有效地抑制Hilbert变换中的端点效应,获得准确的瞬时频率和瞬时幅值,从而得到具有物理意义的Hilbert谱。对仿真和实际信号的分析结果表明,基于支持矢量回归机的数据序列延拓方法能有效地解决Hilbert-Huang变换中存在的端点效应问题,而且其效果优于基于神经网络的数据序列延拓方法。  相似文献
3.
基于Hilbert变换的包络分析及其在机械故障诊断中的应用   总被引:8,自引:1,他引:7  
本文讨论了Hilbert变换的基本原理,以及基于Hilbert变换的包络解调方法在机械故障诊断中的应用。实践表明:对于具有调制现象的设备故障诊断,基于Hilbert变换的包络解调方法,具有明显的诊断意义,是一种可靠的诊断方法。  相似文献
4.
Multicomponent AM–FM demodulation is an available method for machinery fault vibration signal analysis, so a new method for mechanical fault diagnosis based on iterated Hilbert transform (IHT) is proposed. The principle of computing the asymptotically exact multicomponent sinusoidal model for an arbitrary signal by iterating Hilbert transform is introduced, and some properties of IHT are analyzed. Theoretical analysis for the generic two-component signal shows that there are limitations in the direct estimation of instantaneous frequencies via the phase signals of the previously obtained model. Therefore, a smoothed instantaneous frequency estimation (SIFE) method based on difference operator and zero-phase digital low-pass filtering is proposed, and then the accuracy and validity of this method have been proved by the simulation results. The analysis results of the mechanical fault signals show that the weak features of these signals can be efficiently extracted with the proposed approach.  相似文献
5.
齿轮箱故障诊断中信号解调方法的研究   总被引:4,自引:0,他引:4  
提出了一种对齿轮箱调制类故障信号进行诊断的综合方法,对于既有调幅成分又有调频成分的齿轮箱故障信号,提出首先利用Hilbert变换解调出包络信息,同时保留剩余信号,然后用三次FFT技术对调频信息进行解调,使得调频信号特征更加清晰,为齿轮箱故障诊断提供了更准确的信息。  相似文献
6.
A signal decomposition or lowpass filtering with Hilbert transform?   总被引:4,自引:0,他引:4  
Recently, Chen and Wang discovered an explicit formula that makes use of the Hilbert transform for accurate decomposition of a lower harmonic from a signal composition. This letter presents another proof with a new interpretation for the formula using the Bedrosian identity for overlapping signals. This new and simpler proof is based only on the Hilbert transform and does not involve presentation of the Fourier transform. As a result the discovered formula is introduced as a lowpass filter suitable for non-stationary signals.  相似文献
7.
希尔伯特变换原理在轴承故障诊断中的应用   总被引:3,自引:0,他引:3  
阐述希尔伯特变换及解调的基本原理,并据此对振动信号进行幅值及相位解调与分析,为旋转机械故障诊断提供早期和准确的故障信息。  相似文献
8.
基于EMD和频谱校正的故障诊断方法   总被引:3,自引:2,他引:1  
提出了一种基于短时间样本的故障诊断方法,通过频谱校正提高频谱精度.首先对原始信号进行小波降噪,提高信噪比;然后进行经验模态分解,获取信号的各阶本征模态函数;分别对各阶本征模态函数进行希尔伯特解调分析,获得包含系统故障特征信息的调制信号;接着采用校正算法对调制信号进行频谱校正,频谱变换后获得精确的频谱;最后根据校正结果进行系统故障判别.实践表明,此方法具有速度快、精度高的特点,适合于设备的在线快速诊断.  相似文献
9.
Hilbert transform in vibration analysis   总被引:3,自引:0,他引:3  
This paper is a tutorial on Hilbert transform applications to mechanical vibration. The approach is accessible to non-stationary and nonlinear vibration application in the time domain. It thrives on a large number of examples devoted to illustrating key concepts on actual mechanical signals and demonstrating how the Hilbert transform can be taken advantage of in machine diagnostics, identification of mechanical systems and decomposition of signal components.  相似文献
10.
Signal processing is an important tool for diagnostics of mechanical systems. Many different techniques are available to process experimental signals, among others: FFT, wavelet transform, cepstrum, demodulation analysis, second order ciclostationarity analysis, etc. However, often hypothesis about data and computational efforts restrict the application of some techniques. In order to overcome these limitations, the empirical mode decomposition has been proposed. The outputs of this adaptive approach are the intrinsic mode functions that are treated with the Hilbert transform in order to obtain the Hilbert-Huang spectrum.Anyhow, the selection of the intrinsic mode functions used for the calculation of Hilbert-Huang spectrum is normally done on the basis of user’s experience. On the contrary, in the paper a merit index is introduced that allows the automatic selection of the intrinsic mode functions that should be used. The effectiveness of the improvement is proven by the result of the experimental tests presented and performed on a test-rig equipped with a spiral bevel gearbox, whose high contact ratio made difficult to diagnose also serious damages of the gears. This kind of gearbox is normally never employed for benchmarking diagnostics techniques. By using the merit index, the defective gearbox is always univocally identified, also considering transient operating conditions.  相似文献
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