Wireless Concrete Strength Monitoring of Wind Turbine Foundations

Area of Science:

• Civil Engineering
• Materials Science
• Structural Health Monitoring

Background:

• Wind turbine foundations cast in place mature under variable environmental conditions, leading to performance uncertainty.
• This uncertainty can result in over-designed foundations and inaccurate structural health prognoses.

Purpose of the Study:

• To demonstrate the field application of a dense, wireless thermocouple network for monitoring concrete strength development in wind turbine foundations.
• To provide a practical alternative to computational models for assessing foundation performance.

Main Methods:

• Utilized a dense, wireless thermocouple network to monitor temperature evolution in an onshore, reinforced-concrete wind turbine foundation over 29 days.
• Applied advanced fly ash concrete strength and maturity modeling to estimate strength distribution and evolution.
• Verified strength estimates using core samples.
• Employed an artificial neural network trained on temperature data to estimate distributed concrete strengths from sparse sensor data.

Main Results:

• Successfully monitored the strength development of a wind turbine foundation in real-time.
• Accurately estimated concrete strength distribution and evolution using temperature data and modeling.
• Demonstrated that artificial neural networks can estimate distributed strengths from sparse thermocouple data.

Conclusions:

• The developed techniques offer a practical and effective method for monitoring wind turbine foundation concrete strength.
• This approach can assist site operators in making informed decisions regarding foundation design, construction, operation, and maintenance.
• The study highlights the potential of wireless sensor networks and AI in structural health monitoring of critical infrastructure.