EMD与高阶累积量在滚动轴承故障诊断中的应用

共振解调是滚动轴承故障诊断中最常用的方法之一,但由于滚动轴承的早期故障信号中含有强烈的背景噪声，诊断效果不够明显。为此，提出一种基于EMD（Empirical Mode Decomposition）与高阶累积量(HOC)的滚动轴承早期故障诊断新方法。该方法首先对故障信号进行EMD分解获得多个基本模式分量，然后对各分量进行高阶累积量分析，并进行重构，最后运用包络解调进行故障诊断。故障实例证明，该方法与传统共振解调方法相比，具有较大的优势。

Study on Application of EMD and HOC in Fault Diagnosis for Rolling Bearings

Resonant demodulation is one of the most commonly used methods for rolling bearing fault diagnosis. However, this method is less effective sometimes since the early fault signal contains strong background noise. In this paper, a new denoising method based on empirical mode decomposition (EMD) and high-order cumulative quantities (HOC) is proposed. Fault signals are firstly decomposed into several intrinsic mode functions and then each function is analyzed and reconstructed using higher-order cumulative quantities. Finally, the fault characteristics of rolling bearing are extracted by using resonance demodulation. A practical example of fault diagnosis shows that this method has more preponderant than the traditional resonance demodulation method.