Experimental Evaluation of Wind Turbine Gearbox Structural Models Using Fiber Optic Strain Sensors

Conference paper (2022)

Authors

U. Gutierrez Santiago Team Jan-Willem van Wingerden - Mechanical, Maritime and Materials Engineering , Siemens Gamesa Renewable Energy
X. L. Fuentes Siemens Gamesa Renewable Energy
Alfredo Fernández Sisón Siemens Gamesa Renewable Energy
H. Polinder Siemens Gamesa Renewable Energy
J.W. van Wingerden Siemens Gamesa Renewable Energy
Research Group
Team Jan-Willem van Wingerden (Mechanical, Maritime and Materials Engineering) (TU Delft)
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Published Date

2022

Language

English

Reuse Rights

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Jan-Willem van Wingerden

Abstract

Wind turbine technology has seen remarkable advancements in the last decades. Most notably, the rated power and size of wind turbines have grown considerably to reduce the cost of energy from wind. The increase in rotor diameters has pushed gearbox manufacturers to introduce multiple technological innovations to boost the torque density of current designs. One of the critical challenges of next-generation gearbox designs is to optimize structural components and gears. Complex models are needed to predict the gearbox components' load-carrying capacity and fatigue life. These tools need to be demonstrated and validated through experimental evaluation. Through physical testing, this study evaluates the structural calculation models used for a modern 6MW wind turbine gearbox. The measurement system is composed of fifty-four fiber Bragg gratings. Optical strain sensors have been used because they offer a higher signal-to-noise ratio, are immune to electromagnetic interference, and allow a more straightforward installation than conventional electrical strain gauges. A good correlation between the structural models and the test results in a full-scale back-to-back test bench has been achieved. This enables studying the effect of a range of design parameters through simulations. Hence, without the need to carry out physical testing for each design. Increasing the confidence in structural models through experimental data leads to more optimized gearbox designs and significant improvements in torque density and overall cost of the gearbox.