Fault Diagnosis of Distributed Parameter Systems Modeled by Linear Parabolic PDEs with State Faults

[+] Author and Article Information
Hasan Ferdowsi

Electrical Engineering Department, Texas A&M University – Texarkana 7101 University Ave, Texarkana, TX 75503, USA

Sarangapani Jagannathan

Department of Electrical & Computer Engineering, Missouri University of Science and Technology 301 W 16th st, Rolla, MO 65409, USA

1Corresponding author.

ASME doi:10.1115/1.4037332 History: Received June 05, 2016; Revised July 10, 2017


In this paper, the problem of fault diagnosis in distributed parameter systems (DPS) is investigated. The behavior of DPS is best described by partial differential equation (PDE) models. In contrast to transforming the DPS into a finite set of ordinary differential equations (ODE) prior to the design of control or fault detection schemes by using significant approximations thus reducing the accuracy and reliability of the overall system, in this paper, the PDE representation of the system is directly utilized to construct a fault detection observer. A fault is detected by comparing the detection residual, which is the difference between measured and estimated outputs, with a predefined detection threshold. Once the fault is detected, an adaptive approximator is activated to learn the fault function. The estimated fault parameters are then compared with their failure thresholds to provide an estimate of the remaining useful life of the system. The scheme is verified in simulations on a heat system which is described by parabolic PDEs.

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