This paper presents a benchmark problem for fault diagnosis of an internal combustion engine that has been formulated and solved. The objective is to design a diagnosis system using and incomplete model information training data that only contains a limited set of fault realizations. Six different solutions to the benchmark, that were presented at the IFAC Safeprocess symposium 2024, are described and evaluated. The contribution of this paper is the benchmark and the presentation of six different solutions in one paper. The paper is intended to provide a starting point for engineers and researchers who work with fault diagnosis and monitoring of technical systems.

A fault diagnosis benchmark of technical systems with incomplete data — six solutions

Forouzanfar, Mehdi;Pinnarelli, Anna;
2025-01-01

Abstract

This paper presents a benchmark problem for fault diagnosis of an internal combustion engine that has been formulated and solved. The objective is to design a diagnosis system using and incomplete model information training data that only contains a limited set of fault realizations. Six different solutions to the benchmark, that were presented at the IFAC Safeprocess symposium 2024, are described and evaluated. The contribution of this paper is the benchmark and the presentation of six different solutions in one paper. The paper is intended to provide a starting point for engineers and researchers who work with fault diagnosis and monitoring of technical systems.
2025
Data-driven fault diagnosis
Fault detection and isolation
Model-based diagnosis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/392130
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