噪声与振动控制2016，Vol.36Issue(5)：144-149,6.DOI:10.3969/j.issn.1006-1335.2016.05.030
基于机匣振动信号的滚动轴承故障特征提取
Fault Feature Extraction of Rolling Bearings Based on Casing Vibration Signals
摘要
Abstract
Fault feature extraction of rolling bearings based on casing vibration signal is studied. The experiment for the fault simulation of the rolling bearings is done and the vibration signals of the bearing base and casing are acquired. Analysis results show that, compared to the bearing base, the vibration signal of the casing is complex and the fault feature of the bearing is not obvious. The envelope demodulation method cannot extract the fault characteristics directly. Therefore, the singular value decomposition (SVD) is employed to process the vibration signal. It is found that the singular values at different peaks in the difference spectrum can represent the signals of different components. The singular value reconstruction signal at the first peak always represents the components of the rotating frequency and modulation signals when the fault signals of the bearing are weak. The fault modulation signals can be effectively extracted by selecting the singular values after the first peak in the difference spectrum. This study provides a new method for the fault feature extraction of rolling bearings based on the vibration signals of casing.关键词
振动与波/滚动轴承/机匣测点/故障特征提取/奇异值分解/差分谱Key words
vibration and wave/rolling bearing/casing measurement point/fault feature extraction/singular value decomposition (SVD)/difference spectrum分类
信息技术与安全科学引用本文复制引用
韩特,蒋东翔,付道鹏..基于机匣振动信号的滚动轴承故障特征提取[J].噪声与振动控制,2016,36(5):144-149,6.基金项目
国家自然科学基金资助项目 （）
