文章引用说明 更多>> (返回到该文章)

陈汉新, 王庆军, 陈绪兵等. 基于解调振动信号特征提取齿轮箱的故障诊断[J]. 武汉工程大学学报, 2010, 32(9): 67-77.

被以下文章引用:

  • 标题: 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

    关键字: 齿轮箱, EEMD, 能量熵, 幅值, 分解次数Gearbox; EEMD; Energy Entropy; Amplitude; Ensemble Number

    期刊名称: 《Mechanical Engineering and Technology》, Vol.1 No.4, 2012-12-19

    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.

在线客服:
对外合作:
联系方式:400-6379-560
投诉建议:feedback@hanspub.org
客服号

人工客服,优惠资讯,稿件咨询
公众号

科技前沿与学术知识分享