The LiU-ICE Benchmark -- An Industrial Fault Diagnosis Case Study

TL;DR

The LiU-ICE benchmark offers a comprehensive dataset and model for industrial fault diagnosis, aiding research by simulating real engine faults and supporting model development and evaluation.

Contribution

This paper introduces the LiU-ICE benchmark, including data and a model for fault diagnosis in internal combustion engines, facilitating research and evaluation in industrial fault detection.

Findings

Data collected from engine test bench in nominal and faulty modes

A state-of-the-art model of the engine air path provided

Used in a major fault diagnosis competition

Abstract

This paper presents the LiU-ICE fault diagnosis benchmark. The purpose of the benchmark is to support fault diagnosis research by providing data and a model of an industrially relevant system. Data has been collected from an internal combustion engine test bench operated in both nominal and faulty modes. A state-of-the-art model of the air path through an internal combustion engine with unknown parameters is provided. This benchmark has previously been used in a competition at the 12th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes (Safe Process) 2024, Ferrara, Italy.