中国电机工程学报Issue(16)：4147-4152,6.DOI:10.13334/j.0258-8013.pcsee.2015.16.018
基于复数小波多尺度包络分析的风机滚动轴承故障特征提取
Application of the Complex Wavelet Analysis in Fault Feature Extraction of Blower RollingBearing
摘要
Abstract
The method of multi-scale enveloping spectrogram based on complex wavelet was proposed for feature value extraction of rolling bearing faults. It combines the band-pass filtering and envelope analysis of the measured vibration signals into a single-step operation and overcomes the shortcoming of the conventional envelope analysis in which the resonance frequency of the bearing should be known in advance. The case study of blower bearing shows that the proposed approach is suitable for identification of bearing fault under complicated running condition. The feature value from vertical slice of the multi-scale enveloping spectrogram at rotating frequency is the most sensitive to a bearing fault.关键词
复数小波变换/多尺度包络分析/风机/滚动轴承/故障诊断Key words
complex wavelet/multi-scale envelope analysis/blower/rolling bearing/fault diagnosis分类
能源科技引用本文复制引用
潘作为,梁双印,李惊涛,柳亦兵..基于复数小波多尺度包络分析的风机滚动轴承故障特征提取[J].中国电机工程学报,2015,(16):4147-4152,6.基金项目
国家自然科学基金项目(51305135)；中国华能集团科技项目(HNKJ13-H20-05)。 Project Supported by National Natural Science Foundation of China (51305135) （51305135）
The China Huaneng Group Science and Technology Program (HNKJ13-H20-05) （HNKJ13-H20-05）
