# [1]高清清,贾民平.基于EEMD的奇异谱熵在旋转机械故障诊断中的应用[J].东南大学学报(自然科学版),2011,41(5):998-1001.[doi:10.3969/j.issn.1001-0505.2011.05.020] 　Gao Qingqing,Jia Minping.EEMD method based singular value spectral entropy in fault diagnosis of rotating machinery[J].Journal of Southeast University (Natural Science Edition),2011,41(5):998-1001.[doi:10.3969/j.issn.1001-0505.2011.05.020] 点击复制 基于EEMD的奇异谱熵在旋转机械故障诊断中的应用() 分享到： var jiathis_config = { data_track_clickback: true };

41

2011年第5期

998-1001

2011-09-20

## 文章信息/Info

Title:
EEMD method based singular value spectral entropy in fault diagnosis of rotating machinery

(东南大学机械工程学院,南京 211189)
Author(s):
(School of Mechanical Engineering, Southeast University, Nanjing 211189,China)

Keywords:

TH17;TP206
DOI:
10.3969/j.issn.1001-0505.2011.05.020

Abstract:
For the non-stationary and non-linear characteristics of rotating machinery vibration signal, ensemble empirical mode decomposition(EEMD) method based singular value spectral entropy is proposed for signal analysis and fault diagnosis of rotating machinery. This method utilizes the advantage of EEMD which can effectively restrain model mixing. First, the EEMD method is used to decompose the original signal to obtain intrinsic mode functions (IMFs). Then, a feature pattern matrix is created by intrinsic mode functions. Finally, the singular spectrum entropy of the feature pattern matrix is calculated, since singular spectrum entropy can reflect the system’s working condition and fault type. Singular value spectral entropy based on the EMD method and the EEMD method are respectively used to analyze and compare the turning chatter vibration signals. The result verifies that the proposed method is effective and feasible.

## 参考文献/References:

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