Distributed model-based sensor fault diagnosis of marine fuel engines

Journal Article (2022)
Author(s)

N. Kougiatsos (TU Delft - Mechanical Engineering)

R.R. Negenborn (TU Delft - Mechanical Engineering)

V. Reppa (TU Delft - Mechanical Engineering)

Research Group
Transport Engineering and Logistics
DOI related publication
https://doi.org/10.1016/j.ifacol.2022.07.153 Final published version
More Info
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Publication Year
2022
Language
English
Research Group
Transport Engineering and Logistics
Issue number
6
Volume number
55
Pages (from-to)
347-353
Event
11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2022 (2022-06-08 - 2022-06-10), Pafos, Cyprus
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300
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Abstract

This paper proposes a distributed model-based methodology for the detection and isolation of sensor faults in marine fuel engines. The proposed method considers a Mean Value First Principle model and a wide selection of heterogeneous sensors for monitoring the engine components. The detection of faults is realised based on residuals generated using nonlinear Differential Algebraic estimators combined with adaptive thresholds. The isolation of faults is, then, realised in two levels; local sensor fault detection and isolation agents are designed to monitor specific sensor sets and aim to detect faults in these sets; and a global decision logic is designed to isolate multiple sensor faults that may be propagated between the local monitoring agents. Finally, simulation results are used to illustrate the application of this method and its efficiency.