基于EEMD和共振解调的滚动轴承自适应故障诊断

本文为解决滚动轴承原始振动信号信噪比低以及带通滤波器参数选择依赖于人的主观经验等影响传统共振解调技术有效应用的问题，提出了EEMD自适应消噪和自适应共振解调相结合的方法。论文首先利用EEMD自适应地将信号分解成多个分量，通过互相关系数方法进行自适应重构以突出故障特征信号，然后利用谱峭度自动确定带通滤波器的中心频率和带宽，最后对滤波后的信号进行能量算子解调谱分析。数字仿真信号和滚动轴承实验证明了该方法的有效性。

Adaptive fault diagnosis of rolling bearingsbased on EEMD and demodulated resonance

In order to solve the applicative problem of traditional demodulated resonance technology, such as the low signal to noise ratio of original signal of rolling bearing and the parameter selection of band-pass filter which depends on the experiences of individual, this paper presents a method of fault diagnosis of rolling bearing based on combination adaptive EEMD denoising with adaptive demodulated resonance. Firstly, many components are decomposed via EEMD from original data adaptively, and adaptive reconstruction by using correlation coefficient method to highlight fault characteristic signal. Then the center frequency and bandwidth of band-pass filter are determined by spectral kurtosis. Last, the filtered signal is analyzed by using energy operator demodulation spectrum. Numerical simulation signal and a rolling bearing experiment results show the validity of the proposed method.