Work

Advanced Lifetime Prediction for Wind Turbine Gearboxes: Integrating Non-linear Damage Models with Industry Standards

Year: 2025

Type: article

Abstract: This research presents a Python-based tool designed to improve fatigue life predictions for wind turbine drivetrain components by integrating industry-standard methods with a non-linear fatigue damage accumulation model. The tool applies the L10 method (IEC 61400, ISO 281) for bearings and ISO 6336 for gears, accounting for variable load, speed, and torque spectra. Enhanced by the Aeran damage model, the tool provides a more accurate reflection of damage interactions across stress levels, overcomming the limitations of traditional Miner's rule.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15077028

Authors: Arsalan Muhammad Ahmad, Prof. dr. Kris hectors, Prof. dr. Wim De Waele

Language: English

Topic: Gear and Bearing Dynamics Analysis

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W6911896901

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