摘要
针对轮对轴承故障信息不易提取的特性,提出了基于EEMD的共振解调方法。首先,采用EEMD方法将原始信号分解为17个IMF分量,计算每个分量的峭度值,选取峭度值大于3的IMF分量相加,合成新的信号;然后,对新的合成信号进行谱峭度分析,得到冲击成分所在的频带,并据此设计带通滤波器对合成信号进行滤波处理;最后,对滤波后的信号进行Hilbert变换和频谱分析,提取冲击成分的频率,并与理论故障频率对比,进行故障诊断。分别对外圈故障、滚动体故障、保持架故障的轴承进行振动试验,并利用此方法对试验结果进行分析,结果表明,该方法能够有效地识别列车轮对轴承的故障信息。
For the characteristics of the wheel set bearing fault information is hard to extract,a resonance demodulation method based on ensemble empirical mode decomposition（EEMD）is proposed. The original signal is decomposed into 17 IMF components by EEMD method,and the kurtosis value of each component is calculated. The IMF components whose kurtosis value is greater than 3 are added to composite a new signal. Then the new composite signal is analyzed with spectral kurtosis,and the frequency band where the impacting component is located is obtained. Based on this,a band-pass filter is designed to conduct with filtering processing to the composite signal. Finally the frequency of the impact composition is extracted by Hilbert transformation and spectrum analysis to the filtered signal,and compared with the theoretical fault frequency,then the bearing is proceeded with fault diagnosis. The vibration tests for the bearings of the outer ring fault,rolling body fault,and cage fault were carried on respectively,and the test results are analyzed by using this method. The results show that the method can identify the fault information of the trains＇ wheel set bearing effectively.
出处
《现代电子技术》
北大核心
2015年第21期24-27,共4页
Modern Electronics Technique
关键词
EEMD
峭度
共振解调
故障诊断
EEMD
kurtosis
resonance demodulation
fault diagnosis
