ROTOR FAULT FEATURE EXTRACTION METHOD USING MVMD AND IEDPE (MT)

WU YaoChun; GUO XiaoBo; DU ShaoHua; JU Hai; ZHAO Yan; WU Jie; JIA XiaoFeng

doi:10.16579/j.issn.1001.9669.2023.05.001

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ROTOR FAULT FEATURE EXTRACTION METHOD USING MVMD AND IEDPE (MT)

更新时间：2023-11-16

- ROTOR FAULT FEATURE EXTRACTION METHOD USING MVMD AND IEDPE (MT)
- Journal of Mechanical Strength Issue 5, Pages: 1017-1023(2023)
- 作者机构：
  
  1. 安阳工学院机械工程学院
  2. 安阳市质量技术监督检验测试中心
- 作者简介：
- 基金信息：
- DOI：10.16579/j.issn.1001.9669.2023.05.001
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WU YaoChun, GUO XiaoBo, DU ShaoHua, et al. ROTOR FAULT FEATURE EXTRACTION METHOD USING MVMD AND IEDPE (MT). [J]. Journal of Mechanical Strength (5):1017-1023(2023)
DOI：

WU YaoChun, GUO XiaoBo, DU ShaoHua, et al. ROTOR FAULT FEATURE EXTRACTION METHOD USING MVMD AND IEDPE (MT). [J]. Journal of Mechanical Strength (5):1017-1023(2023) DOI： 10.16579/j.issn.1001.9669.2023.05.001.

摘要

为准确表征转子系统不同运行状态，提出一种改进的变分模态分解(Modified Variational Mode Decomposition, MVMD)与瞬时能量分布排列熵(Instantaneous Energy Distribution Permutation Entropy, IEDPE)结合的转子故障特征量化提取方法。利用相关性阈值策略确定变分模态分解(Variational Mode Decomposition, VMD)分解层参数并设计MVMD算法；然后，将采集到的振动信号输入MVMD中进行分解，计算各模态分量的瞬时能量分布；最后，提取各模态分量IEDPE作为故障量化特征。与MVMD+PE、EMD+IEDPE、EEMD+IEDPE进行对比，结果表明，提取的故障特征可更有效地表征转子故障状态之间的显著差别，使故障类别更准确识别。

Abstract

To accurately characterize the different operating states of the rotor system, a modified variational mode decomposition（MVMD） combined with instantaneous energy distribution permutation entropy（IEDPE） is proposed to quantify and extract rotor fault features. The parameters of the variational mode decomposition（VMD） decomposition layer are determined using correlation threshold strategy and the MVMD algorithm is designed. Then, the acquired vibration signals are input into the MVMD for decomposition and the instantaneous energy distribution of each mode component is calculated. Finally, the IEDPE of each mode component is extracted as the fault quantization feature. Compared with MVMD+PE, EMD+IEDPE, and EEMD+IEDPE, the results show that the fault features extracted by the proposed method are more effective in characterizing significant differences between rotor fault states, allowing more accurate recognition of fault categories.

关键词

特征提取变分模态分解瞬时能量分布排列熵转子故障

Keywords

Feature extractionVariational mode decompositionInstantaneous energy distributionPermutation entropyRotor fault

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