基于AVMD与Teager能量算子的风电机组故障诊断方法
为解决变分模态分解（variational mode decomposition，简称VMD）在噪声情况下提取风电机组故障特征时因参数设置的人为经验不足而带来的误差问题及耗费时间的问题，提出一种基于自适应变分模态分解（adaptive variational mode decomposition，简称AVMD）算法的风电机组故障诊断方法。首先，将包络熵‑峭度‑互信息准则（envelope entropy，kurtosis and mutual information，简称EKM）作为黏菌算法（slime mold algorithm，简称SMA）的适应度函数来寻找最优解，并按照最优解对故障信号...
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| Materyal Türü: | Artigo |
|---|---|
| Dil: | Chinês |
| Baskı/Yayın Bilgisi: |
Editorial Department of Journal of Vibration, Measurement & Diagnosis
2025-04-01
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| Seri Bilgileri: | Zhendong Ceshi yu Zhenduan |
| Konular: | |
| Online Erişim: | https://zdcs.nuaa.edu.cn/zdcsyzd/article/abstract/20250225?st=article_issue |
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