论文部分内容阅读
提出了小波分析与短时傅立叶分析相结合的方法来分析处理滚动轴承的振动信号,提取对应于轴承保持架的特定频率成分有助于准确地判断轴承保持架的健康状况。研究结果表明,在氢涡轮泵低温轴承保持架故障特征辨识中,综合利用小波分析与短时傅立叶分析能够更形象、更直观地识别出特定的频率成分。
The combination of wavelet analysis and short-time Fourier analysis is proposed to analyze and process the vibration signal of the rolling bearing. The extraction of the specific frequency components corresponding to the bearing retainer helps to accurately determine the bearing cage health status. The results show that in the identification of the fault characteristics of the cryogenic bearing cage of a turbo-pump, the combination of wavelet analysis and short-time Fourier analysis can identify the specific frequency components more vividly and intuitively.