A rotor fault diagnosis method based on EEMD cloud model and SVM

TIAN Songfeng; XU Jiarui; WANG Meijun; HAN Qiang

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A rotor fault diagnosis method based on EEMD cloud model and SVM

更新时间：2025-09-28

- A rotor fault diagnosis method based on EEMD cloud model and SVM
- Thermal Power Generation Issue 3, (2017)
- 作者机构：
  
  华北电力大学电站设备状态监测与控制教育部重点实验室,河北,保定,071003
- 作者简介：
- 基金信息：
- DOI：
  CLC： TK268+.1
- Published Online：27 March 2017，
  
  Published：2017
- 稿件说明：
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TIAN Songfeng, XU Jiarui, WANG Meijun, et al. A rotor fault diagnosis method based on EEMD cloud model and SVM[J]. Thermal power generation, 2017, (3).
DOI：

TIAN Songfeng, XU Jiarui, WANG Meijun, et al. A rotor fault diagnosis method based on EEMD cloud model and SVM[J]. Thermal power generation, 2017, (3). DOI：

摘要

提出了一种基于集合经验模态分解（ EEMD）、云模型与支持向量机（ SVM）相结合的汽轮机转子多故障诊断方法。该方法首先采用 EEMD将振动信号分解成若干个 IMF分量，利用相关系数法对 IMF分量进行筛选，然后对筛选后的 IMF分量进行逆向云发生器计算，得到云模型的数字特征并构建为特征向量，将其应用到有向无环图 SVM中进行转子多故障状态识别，并与传统的 EEMD能量法进行对比。结果表明，该方法能够准确地完成转子多故障诊断，具有更高的识别率。

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