| DigiWind

Structural Health Monitoring of Wind Turbines

Course Overview

This module provides a comprehensive introduction to Structural Health Monitoring (SHM) systems for wind turbines, covering the fundamental principles, sensing technologies, and analytical methods used to assess structural condition and detect damage. It presents the complete SHM workflow, including data acquisition, signal processing, feature extraction, and statistical model development, with applications to both onshore and offshore wind energy systems.

Course Highlights

A key focus of the module is on physics-based monitoring approaches, including structural dynamics, vibration-based monitoring, and modal analysis of critical turbine components such as blades, towers, and support structures. The module also explores advanced non-destructive evaluation techniques, particularly ultrasonic and wave-based methods for identifying defects in composite materials and other structural elements. In addition, selected data-driven methods, including pattern recognition and machine learning techniques for anomaly detection, are introduced.

MAIN GOAL

The primary goal of the module is to equip learners with the knowledge and skills required to design, implement, and interpret SHM systems for wind turbines. By addressing practical considerations such as sensor selection, environmental variability, and system integration, the module aims to support improved structural reliability, early damage detection, and the adoption of effective condition-based maintenance strategies within the wind energy sector.

Learning Outcomes

After completion of this course, you will gain the ability to:

+ Explain the principles and objectives of Structural Health Monitoring (SHM) and evaluate its role in improving the reliability, safety, and maintenance of wind turbine systems.
+ Describe and assess sensing technologies used in SHM, including accelerometers, strain gauges, ultrasonic sensors, and other monitoring devices applicable to wind turbine structures.
+ Apply signal processing and feature extraction techniques to structural response data for damage detection and condition assessment.
+ Analyze the dynamic behavior of wind turbine structures using vibration-based monitoring methods, structural dynamics concepts, and modal analysis techniques
+ Develop and interpret statistical and data-driven models for anomaly detection, damage identification, and condition monitoring.