Publication

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

Journal Article (2025)

Journal

Control Engineering Practice

Pages

106427

Volume

164

Doc link

https://doi.org/10.1016/j.conengprac.2025.106427

File

Download the digital copy of the doc pdf document

Authors

  • Jung, Daniel

  • Frisk, Erik

  • Krysander, Mattias

  • Sztyber-Betley, Anna

  • Corrini, Francesco

  • Arici, Andrea

  • Anselmi, Nicolas

  • Mazzoleni, Mirko

  • Xu, Jiamin

  • Mo, Siwen

  • Xu, Zixuan

  • Yang, Chongpan

  • Du, Zhile

  • Safaeipour, Hossein

  • Forouzanfar, Medhi

  • Mirahi, Vahid

  • Pinnarelli, Anna

  • Puig Cayuela, Vicenç

  • Deng, Qiao

  • Liu, Yufei

  • Liu, Jiakun

  • Ke, Haobin

  • Zhu, Wanting

  • Merkelbach, Silke

  • Ahang, Maryam

  • Najjaran, Homayoun

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.

Categories

control theory.

Author keywords

Fault detection and isolation, Model-based diagnosis, Data-driven fault diagnosis

Scientific reference

D. Jung, E. Frisk, M. Krysander, A. Sztyber-Betley, F. Corrini, A. Arici, N. Anselmi, M. Mazzoleni, J. Xu, S. Mo, Z. Xu, C. Yang, Z. Du, H. Safaeipour, M. Forouzanfar, V. Mirahi, A. Pinnarelli, V. Puig, Q. Deng, Y. Liu, J. Liu, H. Ke, W. Zhu, S. Merkelbach, M. Ahang and H. Najjaran. A fault diagnosis benchmark of technical systems with incomplete data - six solutions. Control Engineering Practice, 164: 106427, 2025.