Fault Diagnosis of Distributed Parameter Systems Modeled by Linear Parabolic Partial Differential Equations with State Faults
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.
H. Ferdowsi and J. Sarangapani, "Fault Diagnosis of Distributed Parameter Systems Modeled by Linear Parabolic Partial Differential Equations with State Faults," Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, vol. 140, no. 1, American Society of Mechanical Engineers (ASME), Jan 2018.
The definitive version is available at https://doi.org/10.1115/1.4037332
Electrical and Computer Engineering
Keywords and Phrases
Equations of state; Failure analysis; Ordinary differential equations; Partial differential equations; Detection threshold; Distributed parameter systems; Failure thresholds; Fault detection schemes; Linear-parabolic; Ordinary differential equation (ODE); Partial differential equations (PDE); Remaining useful lives; Fault detection
International Standard Serial Number (ISSN)
Article - Journal
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