Fault diagnosis method based on dynamic maximum variance unfolding and one-class support vector machine

DENG Xiaogang; TIAN Xuemin

您当前的位置：

首页 >

文章列表页 >

Fault diagnosis method based on dynamic maximum variance unfolding and one-class support vector machine

更新时间：2025-12-10

- Fault diagnosis method based on dynamic maximum variance unfolding and one-class support vector machine
- CIESC Journal Issue 8, Pages: 2146-2151(2011)
- 作者机构：
  
  中国石油大学（华东）信息与控制工程学院,山东,东营,257061
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Online First：05 August 2011，
  
  Published：05 August 2011
- 稿件说明：
移动端阅览
DENG Xiaogang, TIAN Xuemin. Fault diagnosis method based on dynamic maximum variance unfolding and one-class support vector machine[J]. CIESC Journal, 2011, (8): 2146-2151.
DOI：

DENG Xiaogang, TIAN Xuemin. Fault diagnosis method based on dynamic maximum variance unfolding and one-class support vector machine[J]. CIESC Journal, 2011, (8): 2146-2151. DOI：

摘要

针对工业过程的非线性和动态特性，提出一种基于动态最大方差展开（DMVU）和单类支持向量机（OCSVM）的故障诊断方法DMVU-OCSVM。为了分析数据的动态特性和非线性，应用流形学习技术DMVU提取数据变量中的非线性动态流形特征。基于所提取的流形特征信息建立OCSVM统计模型，并构造非线性监控统计量实时检测过程故障。在连续搅拌反应器（CSTR）系统上的仿真结果说明，本文提出的方法能够比OCSVM更有效地检测过程故障。

Abstract

In order to analyze nonlinear and dynamic characteristics of industrial process

a new method combining dynamic maximum variance unfolding and one-class support vector machine(DMVU-OCSVM)was presented.Manifold learning method DMVU was applied to obtain nonlinear and dynamic manifold features.OCSVM was used to build statistic model based on manifold information and nonlinear monitoring statistic was constructed to detect fault online.The simulation results on continuous stirred tank reactor system showed that the proposed method could detect process fault more effectively.

关键词

Keywords

references

Views

498

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Performance study of gas-liquid vortex separators under low cross-sectional gas velocity

Multi objective optimization of flow and heat transfer characteristics of modified manifold microchannel heat sink based on machine learning

Thermal analysis of phase change suspension jet impinging on wall surface covered with variable-shape porous layer

Thermo-gas-elastic coupling performance analysis of high-speed and high-temperature foil face seals

Study on the residence time distribution characteristics of the TPMS-Diamond static mixer

Related Author

No data

Related Institution

No data

⁰