摘要
分析了齿轮与滚动轴承故障振动信号的特征,利用小波变换的分解和重构算法,有效地提取出齿轮与滚动轴承故障特征信号,得到实验结果.通过比较频谱分析和小波分析的特点,有效地证明了小波分析在微弱故障信号提取中的优势.
Vibration fault feature of gear and rolling axletree is analyzed. By using the decomposition and reconstruction algorithm of wavelet transform, the fault feature signal of gear and rolling axletree are extracted availably and the results of experimentation are obtained. The characteristic of spectrum analysis and wavelet analysis are compared, and the predominance of wavelet analysis in extraction of weak fault signal is proved.
出处
《传感技术学报》
CAS
CSCD
北大核心
2007年第5期1196-1198,共3页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金资助项目(60102002)
霍英东基金资助项目(81057)
河北省博士基金资助项目(B2004522)
关键词
小波变换
故障特征提取
齿轮与滚动轴承故障诊断
wavelet transform
extraction of fault characteristic
fault diagnose of gear and rolling axletree