X-ray tomography data of White Etching Cracks (WEC)

Area of Science:

• Materials Science
• Mechanical Engineering
• Tribology

Background:

• Bearing failures in wind turbines can lead to significant downtime and maintenance costs.
• Understanding crack initiation and propagation is crucial for predicting component lifespan.
• Previous research has analyzed crack characteristics, necessitating the underlying data.

Purpose of the Study:

• To provide raw micro-computed tomography (μCT) data of cracks in bearings.
• To serve as a foundation for detailed crack network analysis.
• To support the findings reported in Danielsen et al. (2019).

Main Methods:

• Lab-based micro-computed tomography (μCT) scanning was employed.
• Data acquired from four distinct bearing samples.
• Focus on characterizing internal crack structures and networks.

Main Results:

• Generated a comprehensive dataset of 3D crack morphologies.
• Visualized complex crack networks within bearing materials.
• Quantified crack features relevant to material fatigue.

Conclusions:

• The provided μCT data is essential for validating computational models of crack growth.
• This dataset facilitates further research into bearing degradation mechanisms.
• Contributes to improved predictive maintenance strategies for wind turbine components.