工程科学学报，第37卷，增刊1：65-71,2015年5月 Chinese Journal of Engineering,Vol.37,Suppl.1:65-71,May 2015 DOI:10.13374/j.issn2095-9389.2015.s1.011:http://journals.ustb.edu.cn 基于集合经验模式分解和交叉能量算子的滚动轴承 故障诊断 赵晓宁，冯志鹏 北京科技大学机械工程学院，北京100083 ☒通信作者，E-mail:fengzp@sth.cdu.cn 摘要振动信号的周期性冲击及其重复频率是滚动轴承故障诊断的关键.本文提出了一种基于集合经验模式分解和交叉 能量算子提取滚动轴承故障特征的方法.首先，应用集合经验模式分解方法将振动信号分解为本征模式函数以满足交叉能 量算子对信号单分量的要求.。然后根据相关程度和峭度从本征模式函数中选取敏感分量，计算敏感分量和原始信号的瞬时 交叉能量及其傅里叶频谱.最后根据交叉能量的频谱结构和特征频率识别轴承故障.通过分析滚动轴承故障仿真信号和实 验测试信号，诊新了滚动轴承元件故障，验证了该方法的有效性. 关键词滚动轴承：故障诊断：交叉能量算子；集合经验模式分解 分类号TH165*.3 Fault diagnosis of rolling element bearing based on ensemble empirical mode decompo- sition and cross energy operator ZHAO Xiao-ning,FENG Zhi-peng School of Mechanical Engineering,University of Seience and Technology Beijing.Beijing 100083,China Corresponding author,E-mail:fengzp@ustb.edu.cn ABSTRACT Periodic impulses in vibration signals and its repeating frequency are the key factors for diagnosing rolling element bearing faults.A new method based on ensemble empirical mode decomposition (EEMD)and cross energy operator was proposed to extract the characteristic frequency of bearing fault.Firstly,the signal was decomposed into intrinsic mode function (IMF)by means of EEMD to satisfy the mono-component requirement by the cross energy operator.Next,the sensitive IMF was selected according to correlation and kurtosis,and instantaneous cross energy between the IMF and the original signal and its Fourier spectrum were calcu- lated.Finally,the bearing faults were diagnosed by matching the repeating frequency of fault-induced periodic impulses with the fault characteristic frequency.By analyzing both a simulated faulty bearing vibration signal and the experimental data of bearing faults,the bearing faults were diagnosed and the effectiveness of the proposed method was validated. KEY WORDS rolling element bearing:fault diagnosis:cross energy operator:ensemble empirical mode decomposition 滚动轴承广泛应用于各种机械设备，其工作状态 滚动轴承内圈、外圈、滚动体等元件出现损伤故障 直接影响整个设备的运行效率和使用寿命，但它也是 时，在运行过程中，工作表面损伤点将反复撞击与之接 容易损坏的元件之一·因此，研究滚动轴承故障诊断 触的其他元件表面，产生冲击振动，周期性冲击的重复 具有重要的现实意义 频率即为轴承元件的故障特征频率.分析提取振动信 收稿日期：20150106 基金项目：国家自然科学基金资助项目(11272047)：国家863计划资助项目(2011AA060404):中央高校基本科研业务费专项资金资助项目工程科学学报，第 37 卷，增刊 1: 65--71，2015 年 5 月 Chinese Journal of Engineering，Vol． 37，Suppl． 1: 65--71，May 2015 DOI: 10． 13374 /j． issn2095--9389． 2015． s1． 011; http: / /journals． ustb． edu． cn 基于集合经验模式分解和交叉能量算子的滚动轴承 故障诊断 赵晓宁，冯志鹏 北京科技大学机械工程学院，北京 100083 通信作者，E-mail: fengzp@ ustb． edu． cn 摘 要 振动信号的周期性冲击及其重复频率是滚动轴承故障诊断的关键． 本文提出了一种基于集合经验模式分解和交叉 能量算子提取滚动轴承故障特征的方法． 首先，应用集合经验模式分解方法将振动信号分解为本征模式函数以满足交叉能 量算子对信号单分量的要求． 然后根据相关程度和峭度从本征模式函数中选取敏感分量，计算敏感分量和原始信号的瞬时 交叉能量及其傅里叶频谱． 最后根据交叉能量的频谱结构和特征频率识别轴承故障． 通过分析滚动轴承故障仿真信号和实 验测试信号，诊断了滚动轴承元件故障，验证了该方法的有效性． 关键词 滚动轴承; 故障诊断; 交叉能量算子; 集合经验模式分解 分类号 TH165 + . 3 Fault diagnosis of rolling element bearing based on ensemble empirical mode decompo￾sition and cross energy operator ZHAO Xiao-ning，FENG Zhi-peng School of Mechanical Engineering，University of Science and Technology Beijing，Beijing 100083，China  Corresponding author，E-mail: fengzp@ ustb． edu． cn ABSTRACT Periodic impulses in vibration signals and its repeating frequency are the key factors for diagnosing rolling element bearing faults． A new method based on ensemble empirical mode decomposition ( EEMD) and cross energy operator was proposed to extract the characteristic frequency of bearing fault． Firstly，the signal was decomposed into intrinsic mode function ( IMF) by means of EEMD to satisfy the mono-component requirement by the cross energy operator． Next，the sensitive IMF was selected according to correlation and kurtosis，and instantaneous cross energy between the IMF and the original signal and its Fourier spectrum were calcu￾lated． Finally，the bearing faults were diagnosed by matching the repeating frequency of fault-induced periodic impulses with the fault characteristic frequency． By analyzing both a simulated faulty bearing vibration signal and the experimental data of bearing faults，the bearing faults were diagnosed and the effectiveness of the proposed method was validated． KEY WORDS rolling element bearing; fault diagnosis; cross energy operator; ensemble empirical mode decomposition 收稿日期: 2015--01--06 基金项目: 国家自然科学基金资助项目( 11272047) ; 国家 863 计划资助项目( 2011AA060404) ; 中央高校基本科研业务费专项资金资助项目 滚动轴承广泛应用于各种机械设备，其工作状态 直接影响整个设备的运行效率和使用寿命，但它也是 容易损坏的元件之一． 因此，研究滚动轴承故障诊断 具有重要的现实意义． 滚动轴承内圈、外圈、滚动体等元件出现损伤故障 时，在运行过程中，工作表面损伤点将反复撞击与之接 触的其他元件表面，产生冲击振动，周期性冲击的重复 频率即为轴承元件的故障特征频率． 分析提取振动信