引用本文:陈宣含,沈艳霞,吴定会.风力机系统基于H_/H∞未知输入观测器的故障诊断[J].控制理论与应用,2019,36(10):1690~1697.[点击复制]
CHEN Xuan-han,SHEN Yan-xia,WU Ding-hui.Fault diagnosis of wind turbine system based on H_/H∞ unknown input observer[J].Control Theory and Technology,2019,36(10):1690~1697.[点击复制]
风力机系统基于H_/H∞未知输入观测器的故障诊断
Fault diagnosis of wind turbine system based on H_/H∞ unknown input observer
摘要点击 2409  全文点击 1086  投稿时间：2018-10-20  修订日期：2019-02-07
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DOI编号  10.7641/CTA.2019.80811
  2019,36(10):1690-1697
中文关键词  传动系统  风力机  未知输入观测器  H_/H∞性能指标
英文关键词  Drive system  Wind Turbine  Unknown input observer  H_/H∞Performance index
基金项目  国家自然科学基金
作者单位E-mail
陈宣含 江南大学物联网技术应用教育部工程研究中心 240496392@qq.com 
沈艳霞* 江南大学物联网技术应用教育部工程研究中心 shenyx@jiangnan.edu.cn 
吴定会 江南大学物联网技术应用教育部工程研究中心  
中文摘要
      针对实际工程中风力机传动系统未知输入难以完全解耦的问题，提出一种基于H_/H∞未知输入观测器（UIO）的故障诊断方法。利用未知输入观测器的等式条件将未知输入分解为可解耦与不可解耦两部分，并将可解耦部分从估计误差中消除。利用H_/H∞性能指标设计未知输入观测器的残差产生器，使残差对未知输入中不可解耦部分具有鲁棒性并对故障信号具有敏感性，并在观测器参数设计过程中引入松弛矩阵，从而实现风力机传动系统传感器的故障诊断。考虑到残差信号的随机特性，采用统计理论确定故障检测阈值，使故障诊断结果更具可靠性。经仿真验证该方法可对风力机传动系统传感器加性故障和乘性故障进行有效诊断。
英文摘要
      In order to solve the problem that the unknown input of the wind turbine drive system is difficult to be fully decoupled，a fault diagnosis method based on H_/H∞ unknown input observer(UIO) is proposed. The unknown input is decomposed into decoupled part and undecoupled part using the equality condition of the unknown input observer, and the decoupled part can be eliminated from the estimation error. The H_/H∞ performance index is used to design the residual generator based on unknown input observer,which makes the residual robust to the undecoupled part of the unknown input and sensitive to the fault signal. And the relaxation matrix is used to design the parameter of the observer, so as to realize the fault diagnosis of sensors in wind turbine drive system. Considering the stochastic characteristics of the residual signal, the threshold of fault detection is determined by statistical theory, which makes the fault diagnosis results more reliable. Simulation results show that this method can effectively diagnose the additive and multiplicative faults of sensors in wind turbine transmission system.