基于迭代Hilbert变换的多分量信号解调方法研究及应用

Multicomponent Demodulation Based on Iterated Hilbert Transform and Its Application

旋转机械系统发生故障时,其振动信号通常为多分量AM-FM信号。针对传统的解调方法在多分量振动信号故障特征提取中的局限性,提出一种利用迭代Hilbert变换(Iterated Hilbert transform,IHT)进行机械故障诊断的新方法。介绍IHT的基本原理;通过对任一两分量的AM-FM信号的分析表明利用IHT得到的相位信息直接估计瞬时频率具有一定的局限性,于是提出基于差分算和零相位数字低通滤波的平滑的瞬时频率估计方法,并通过仿真试验表明,与自适应分割算法和Hilbert-Huang变换相比,该方法具有很高的精度且速度较快。对具有外圈故障的滚动轴承和具有断齿故障的齿轮箱振动信号的分析结果表明,基于IHT的多分量AM-FM信号解调方法能有效地提取机械故障振动信号中的故障特征。

The vibration signals of faulty rotary machinery systems are generally multicomponent AM-FM signals. Aiming at the limitations of conventional demodulation methods for extracting the fault features of multicomponent vibration signals, a new approach for mechanical fault diagnosis based on iterated Hilbert transform （IHT） is proposed. The principle of IHT is introduced. It is seen from the analysis for an arbitrary two-component signals that there are limitations in the direct estimation of instantaneous frequencies with the phase signals obtained by IHT, so a smoothed instantaneous frequency estimation method based on difference operator and zero-phase digital low-pass filtering is proposed, and the simulation testing shows that this method is higher in accuracy and speed compared with the self-adaptive segmentation algorithm and Hilbert-Huang transform. The analysis results of the roller bearing vibration signal with an outer race fault and gearbox vibration signal with an broken teeth fault show that the fault features of mechanical fault signals can be extracted efficiently by using the proposed approach.