摘要
振动信号中的冲击现象及其频率特征是诊断齿轮局部损伤故障的重要依据之一。针对齿轮故障特征提出了一种时间-小波能量谱信号处理方法,它能够有效提取振动信号中冲击成分的时域和频域特征。利用时间-小波能量谱方法分析了正常、磨损、断齿等三种状态的齿轮箱振动信号,并与传统频谱分析方法进行相比。结果表明:时间-小波能量谱不仅可以有效提取故障特征,识别出齿轮箱的故障存在,而且可以清晰地分辨出故障类型及故障元件。
The impulses in vibration signals and their spectral features are important in diagnosing localized damage of gears. A new method, so called time-wavelet energy spectrum, was proposed for gear fault diagnosis. It could extract the features of impulses in both time domain and frequency domain. It was used to analyze the vibration signals of a gearbox under normal, worn and tooth broken statuses. The comparison between the proposed method and the traditional spectral analysis showed that the time-wavelet energy spectrum is effective in extracting the impulse features produced by localized gear damage, and thereby in recognizing and locating the gear faults.
出处
《振动与冲击》
EI
CSCD
北大核心
2011年第1期157-161,共5页
Journal of Vibration and Shock
基金
国家自然科学基金资助项目(10732060
50705007)
教育部留学回国人员科研启动基金项目
关键词
齿轮
故障诊断
小波变换
时间-小波能量谱
gear
fault diagnosis
wavelet transformation
time-wavelet energy spectrum
