Early Detection of Extreme Engine Events (EDE3)

Research project predicts serious engine failures that lead to breakdown

Duration of the project

1.8.2025 – 31.7.2027

Source of funding

Business Finland

Total funding

1 029 998 €

The EDE3 (Early Detection of Extreme Engine Events) project aims to develop a comprehensive framework for the early detection, prediction, and prevention of severe engine failures with focus on large internal combustion engines. Led by Turku University of Applied Sciences in close collaboration with industry partners, EDE3 combines high‑frequency monitoring, advanced simulation models, and real‑time data analysis to significantly improve engine reliability and safety in heavy machinery applications.

The EDE3 project seeks to develop a framework for real-time identification, prediction, and prevention of catastrophic failures in large mechanical engines, particularly internal combustion engines. This work is led by the Computational Engineering and Analysis (COMEA) Research Group and the Power and Engine Research Group at Turku University of Applied Sciences and carried outin collaboration with industry partners such as Wärtsilä, AGCO Power, Nome, Unikie, and EDR&Medeso. The project integrates high-frequency monitoring, advanced fault-simulation modeling, and adaptive signal processing. EDE3 is a Business Finland Co-Research project and contributes to Wärtsilä’s Energy Business and the WISE Veturi Project strengthening cooperation between research and industry.

The EDE3 approach combines experimental engine testing, physics-based modeling, and real-time data analysis to detect engine faults earlier and with greater accuracy than existing systems.

The project is structured into four main work packages:

• experimental engine testing,
• model development,
• process development (scaling solutions to larger engines and new technologies), and
• project management.

Notably, the project leverages destructive engine testing to generate rare failure data, which is essential for validating new predictive diagnostics models.

The methods and frameworks developed are designed to be broadly applicable across various heavy machinery

The anticipated outcomes of EDE3 include enhanced engine reliability, reduced operational risks, improved maintenance practices, and the creation of commercial solutions for predictive diagnostics. The methods and frameworks developed are designed to be broadly applicable across various heavy machinery, positioning the Finnish consortium at the forefront of industrial reliability engineering.