欢迎访问《空军工程大学学报》官方网站!

咨询热线:029-84786242 RSS EMAIL-ALERT
基于多级观测器的液压伺服系统自适应故障检测与隔离
DOI:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

TH17

基金项目:

国防基础科研计划项目资助(JCKY2016205A004)


An Adaptive Multistage Observer in Detecting and Isolating Fault in Hydraulic Servo System
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    针对传统的基于固定阈值的故障检测及诊断方法虚警率高,无法有效实现液压伺服系统的故障检测与隔离,提出了一套基于多级观测器的液压伺服系统自适应故障检测与隔离方法。首先,采用第1级RBF网络作为液压伺服系统观测器,通过比较观测器估计输出值与实际系统输出得到残差信号。其次,采用第2级RBF神经网络产生自适应阈值,实现了液压伺服系统自适应故障检测。最后,采用小波包分析提取残差信号特征,利用第3级RBF神经网络实现系统的典型故障隔离。实验结果表明,利用多级观测器模型能够有效实现液压伺服系统的自适应故障检测及隔离。

    Abstract:

    Aimed at the problems that the traditional fault detection and diagnosis methods based on fixedthreshold have a high false alarm rate and fail to realize effective fault detection and isolation, an adaptive fault detection and isolation method for hydraulic servo system based on multistage observer is presented. The firststage RBF neural network is adopted as a fault observer of the hydraulic servo system, and the residual error signal is generated by comparing the estimated observer output with the actual measurements. The secondstage RBF neural network is employed as an adaptive threshold producer, realizing the adaptive fault detection. Features of the residual error signal are extracted by using wavelet packet analysis, and the system fault isolation is made by using the thirdstage RBF neural network. The experimental results show that the multistage observer is effective in detecting and isolating the failure in the hydraulic servo system.

    参考文献
    相似文献
    引证文献
引用本文

沈新刚, 吕镇邦, 孙倩.基于多级观测器的液压伺服系统自适应故障检测与隔离[J].空军工程大学学报,2020,21(5):36-42

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2020-11-26
  • 出版日期: