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

TIAN Songfeng; XU Jiarui; WANG Meijun; HAN Qiang

English

您当前的位置：

首页 >

文章列表页 >

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

Thermal Power Generation Vol. 46, Issue 4, Pages: 111-114(2017)

更新时间：2025-09-28

- A rotor fault diagnosis method based on EEMD cloud model and SVM
- 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
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM621.3
- Published：2017
- 稿件说明：
移动端阅览
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, 46(4): 111-114.
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, 46(4): 111-114. 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。

Abstract

A multi-fault diagnosis method for steam rotors based on ensemble empirical mode decomposition(EEMD)

cloud model and support vector machine(SVM) was proposed. This method firstly uses the EEMD to decompose the vibration signals into several IMF components and the correlation coefficient method to screen the IMF components. Then

it applies the backward cloud generator algorithm to compute the screened IMF components and obtains digital characteristics of the cloud model to build the feature vector. Finally

the feature vector is applied to the directed acyclic graph SVM to perform multi-fault state recognition for the rotors

and the result is compared with that of the conventional EEMD energy method. The experimental results show that

this method can accurately complete multi-fault diagnosis for the rotors and has more accurate recognition rate.

关键词

Keywords

references

Views

252

下载量

CSCD

Alert me when the article has been cited

提交

Publicity Resources

SIMPLIFIED FINITEELEMENT CALCULATION MODEL OF TEMPERATURE FIELD FOR STEAM TURBINE ROTOR

MULTISENSOR INFORMATION MERGING TECHNOLOGY AND IT'S APPLICATION IN VIBRITION FAULT DIAGNOSIS OF ROTARY MACHINES

DEVELOPMENT OF PORTABLE DYNAMIC BALANCING AND VIBRATION ANALYSING SYSTEM FOR ROTARY MACHINES

SHAFTING VIBRATION ANALYSIS AND DYNAMIC BALANCING IN THE FIELD OF A PULSED MOTOR-DRIVEN GENERATOR

APPLICATION OF EXTENDED Petri NETWORK INTO FAULT DIAGNOSIS OF THERMAL POWER UNITS

Related Author

LUO Juan

HU Niansu

QI Haitao

JIN Fenghua

LI Luping

ZHANG Jin-ping

HUANG Shu-hong

HE Gou-qiang (Central China University of Science & Technology

Related Institution

Wuhan University

Changsha University of Science and Technology

Huazhong University of Science and Technology

Dongfang Power Station Technical Renovation Co., Ltd

AI问答

⁰