FDH NDT Research Engineer III, Joshua Scott, will present a scientific poster titled “Ultrasonics and Machine Learning. The Relationship Solving your Bolt Tension Needs.” at the American Clean Power Offshore Wind Conference, October 18, from 4:30-6 pm.
Offshore wind turbines have unique maintenance challenges due to their location and environmental conditions, indicating a need for preventative maintenance to reduce costs associated with maintaining these structures. Like onshore turbines, maintaining correct flange bolt tension is essential to ensuring integrity and stability. Existing ultrasound methods require unstressed bolt length measurements, making it difficult to predict tension on an existing structure’s bolts.
In his presentation, Scott proposes a nondestructive testing (NDT) approach using the relationship between longitudinal and shear wave time of flights (ToFs) to predict bolt tension without requiring unstressed measurements or reference signals. Advanced machine learning-based modeling ensures quality data is collected with minimal technician training and offers interpolative/extrapolative predictions on previously untested bolts. All data is stored for future reference enabling the development of proactive maintenance methods using historical data analytics. Repeatability studies using the proposed method resulted in an average error of 9.127 Kips, and 98% of the tension predictions had less than 10% error (relative to yield stress).
Learn more about the event here.
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