摘要
提出了一种研究旋转机械瞬态信号的分析方法.对齿轮箱加速时测得的原始振动信号进行角域重采样,并对角域里的信号进行经验模式分解(EMD)得到多个固有模式函数(IMF),最后对包含齿轮故障信息的IMF分量进行阶次谱分析.结果表明,阶次跟踪技术能够有效地避免传统频谱方法所无法解决的频率模糊现象,EMD方法能够提取包含故障信息的IMF分量,将两种方法相结合是对传统的频谱分析法的有力补充,具有很广阔的应用前景.
An analysis method on instantaneously signals in the rotate mechanism was explored. The originality vibration signals at start-up in the gearbox are resampled in angle-domain and the results are decomposed with empirical mode decomposition (EMD), and then the many intrinsic mode function (IMF) components are obtained. The IMF component, which contains the fault information of gear, is analyzed with order spectrum analysis. The outcome shows that using order tracking technology can effectively avoid the "frequency smear" phenomenon, which can not be solved with the traditional frequency spectrum method. The IMF component, which contains the fault information, can be extracted with EMD. It is a trenchant supplement for traditional spectrum analysis combining the order tracking with EMD, which has a vast application prospect.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2007年第9期1529-1532,共4页
Journal of Shanghai Jiaotong University
基金
国家自然科学基金(50375157)
军械工程学院创新基金(CXJJ0504)
军械工程学院科研基金(YJJXM07012)资助项目
关键词
阶次跟踪
经验模式分解
齿轮
故障诊断
order tracking
empirical mode decompositior
gear
fault diagnosis