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research-article

Full and Reduced-Order Fault Detection Filter Design with Application in Flow Transmission Lines

[+] Author and Article Information
Saeed Salavati

Department of Mechanical Engineering, University of Houston, Houston, Texas, USA, 77004
ssalavatidezfuli@uh.edu

Karolos Grigoriadis

Department of Mechanical Engineering, University of Houston, Houston, Texas, USA, 77004
karolos@uh.edu

Matthew Franchek

Department of Mechanical Engineering, University of Houston, Houston, Texas, USA, 77004
mfranchek@uh.edu

Reza Tafreshi

Associate Professor, Department of Mechanical Engineering, Texas A&M University at Qatar, Doha, Qatar
reza.tafreshi@qatar.tamu.edu

1Corresponding author.

ASME doi:10.1115/1.4041383 History: Received March 07, 2018; Revised August 30, 2018

Abstract

The full and reduced-order fault detection filter design is examined for fault diagnosis in linear time-invariant (LTI) systems in the presence of noise and disturbances. The fault detection filter design problem is formulated as an H8 problem using a linear fractional transformation (LFT) framework and the solution is based on the bounded real lemma (BRL). Necessary and sufficient conditions for the existence of the fault detection filter are presented in the form of linear matrix inequalities (LMIs) resulting in a convex problem for the full-order filter design and a rank-constrained nonconvex problem for the reduced-order filter design. By minimizing the sensitivity of the filter residuals to noise and disturbances, the fault detection objective is fulfilled. A reference model can be incorporated in the design in order to shape the desired performance of the fault detection filter. The proposed fault detection and isolation (FDI) framework is applied to detect instrumentation and sensor faults in fluid transmission and pipeline systems. To this end, a lumped parameter framework for modeling infinite-dimensional fluid transient systems is utilized and a low-order model is obtained to pursue the instrumentation fault diagnosis objective. Full and reduced-order filters are designed for sensor fault detection and isolation. Simulations are conducted to assess the effectiveness of the proposed fault detection approach.

Copyright (c) 2018 by ASME
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