Monitoring, modelling condition and lifetime

When: Thursday, 1 June 2023, 11:05 - 12:35
Where: Forum 1

Session chair

José Vidal

Product Manager, UL Solutions

Presentations

Optimizing lifetime strategies – how mast, SCADA data and digitalization can make the difference?

Cyrille Huant

Project Manager - Asset Advisory Services, UL Services

Machine Learning-Based Prediction of Mass Imbalance in Wind Turbines: A Key Step Towards Optimizing Operation and Maintenance

Guhan velupillai Gowthaman Malarvizhi

Software Development Engineer - Machine Learning, FormFactor Inc

A Statistical Method for Condition Monitoring to Confidently and Expediently Identify Mechanical Defects from Normal Behaviour Models

Philip Bradstock

Head of Analytics, Bitbloom Ltd

Predictive Maintenance of wind turbine rotor blades based on real time monitoring using acoustic emission technology

Valery Godinez-Azcuaga

Vice President Engineering & Product Development, MISTRAS Group

Forecasting Leading Edge erosion progression by combining blade image data and physics inferred models

Wen Wu

PhD Researcher, University of Nottingham