EEMD能量熵分析及在齿轮箱故障诊断中的应用  

Application of EEMD Energy Entropy Method to Fault Diagnosis of Gearbox

作　　者：石智云 贾民平[1] 

机构地区：[1]东南大学机械工程学院,南京

出　　处：《机械工程与技术》2012年第4期61-67,共7页Mechanical Engineering and Technology

基　　金：国家自然科学基金项目(51075070、51075069、51005047);国家十一五863项目(007AA04Z421);江苏省产学研创新资金计划(BY2009152)。

摘　　要：针对齿轮箱振动信号的非平稳、非线性等特点,提出一种基于总体平均经验模态分解EEMD的能量熵信号分析及故障诊断方法。该方法利用EEMD方法能够有效抑制模式混叠现象的特点,先对原始振动信号进行EEMD分解,得到各阶本征模态函数(IMFs),然后求得将各阶本征模态函数的能量及其熵。指出能量熵的值能够反映系统的工作状态和故障类型。通过对白噪声幅值及分解次数对齿轮箱振动加速度信号分析对比,得出最优化选择方案。For the non-stationary and non-liner characteristics of gearbox vibration signal, ensemble empirical mode decomposition (EEMD) method based energy entropy is proposed for signal analysis and fault diagnosis of gearbox. This method utilizes the advantage of EEMD which can effectively restrain model mixing. Firstly, EEMD method is used to decompose the original signal to get intrinsic mode functions (IMFs). Then, energy of each IMF is calculated. Finally, the energy entropy IMFs is obtained, since energy entropy can reflect the system’s working condition and fault type. The number of ensemble and the amplitude of the added white noise are two parameters need to be set. Different parameters are analyzed in gearbox vibration signals with comparison, aiming at a best choice.

关 键 词：齿轮箱 EEMD 能量熵 幅值 分解次数 

分 类 号：TH13[机械工程—机械制造及自动化]