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Sistema de detecção e isolamento de falhas em sistemas dinâmicos baseado em identi#64257;cação paramétrica

机译:基于参数辨识的动态系统故障检测与隔离系统

摘要

The present research aims at contributing to the area of detection and diagnosis of failure through the proposal of a new system architecture of detection and isolation of failures (FDI, Fault Detection and Isolation). The proposed architecture presents innovations related to the way the physical values monitored are linked to the FDI system and, as a consequence, the way the failures are detected, isolated and classified. A search for mathematical tools able to satisfy the objectives of the proposed architecture has pointed at the use of the Kalman Filter and its derivatives EKF (Extended Kalman Filter) and UKF (Unscented Kalman Filter). The use of the first one is efficient when the monitored process presents a linear relation among its physical values to be monitored and its out-put. The other two are proficient in case this dynamics is no-linear. After that, a short comparative of features and abilities in the context of failure detection concludes that the UFK system is a better alternative than the EKF one to compose the architecture of the FDI system proposed in case of processes of no-linear dynamics. The results shown in the end of the research refer to the linear and no-linear industrial processes. The efficiency of the proposed architecture may be observed since it has been applied to simulated and real processes. To conclude, the contributions of this thesis are found in the end of the text
机译:本研究旨在通过提出故障检测和隔离(FDI,故障检测与隔离)的新系统架构的建议,为故障检测和诊断领域做出贡献。所提出的体系结构提出了与监视的物理值与FDI系统链接的方式有关的创新,因此,也与故障的检测,隔离和分类方式有关。对能够满足所提出的体系结构的目标的数学工具的搜索已经指出了卡尔曼滤波器及其派生的EKF(扩展卡尔曼滤波器)和UKF(无味卡尔曼滤波器)的使用。当被监视的过程在其要监视的物理值和输出之间呈现线性关系时,第一方法的使用非常有效。另外两个是有效的,以防这种动力学是非线性的。然后,在故障检测的背景下简短地比较功能和特性,得出的结论是,在非线性动力学过程中,UFK系统比EKF更好,可以构成提出的FDI系统的体系结构。研究结束时显示的结果涉及线性和非线性工业过程。由于已将其应用于模拟和实际过程,因此可以观察到所提出的体系结构的效率。总而言之,本文的最后部分是本文的贡献。

著录项

  • 作者

    Silva Diego Rodrigo Cabral;

  • 作者单位
  • 年度 2008
  • 总页数
  • 原文格式 PDF
  • 正文语种 por
  • 中图分类

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