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Asset management modelling approach integrating structural health monitoring data for composite components of wind turbine blades

Wu, Wen; Saleh, Ali; Remenyte-Prescott, Rasa; Prescott, Darren; Ruano, Manuel Chiachio; Chronopoulos, Dimitrios

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Authors

Wen Wu

Ali Saleh

Manuel Chiachio Ruano

Dimitrios Chronopoulos



Abstract

Optimal asset management strategies for wind turbine blades help to reduce their operation and maintenance costs, and ensure their reliability and safety. Structural health monitoring (SHM) can determine the health state of wind turbine blades through implementing damage identification strategies. The main load-bearing structure spar of the wind turbine blade is inside the structure, and hence difficult to inspect. Advanced SHM techniques, such as guided wave monitoring, can be used to monitor the development of cracks in real-time and provide an early indication of their existence. This paper presents a risk-based maintenance model based on the state information provided by SHM. The model is based on Petri nets, and describes the blade degradation and guided wave monitoring processes, inspection and maintenance works. Fatigue test data of composite components is processed to provide input for the model. The reliability of guided wave monitoring is also assessed. The proposed model is able to predict the condition state and expected number of repairs of composite components for wind turbine blades, which can potentially help in making informed asset management decisions during wind turbine blade operation.

Citation

Wu, W., Saleh, A., Remenyte-Prescott, R., Prescott, D., Ruano, M. C., & Chronopoulos, D. (2022). Asset management modelling approach integrating structural health monitoring data for composite components of wind turbine blades. In Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022) (1385-1392). https://doi.org/10.3850/978-981-18-5183-4_R22-24-242-cd

Conference Name 32nd European Safety and Reliability Conference (ESREL 2022)
Conference Location Dublin, Ireland
Start Date Aug 28, 2022
End Date Sep 1, 2022
Acceptance Date Aug 28, 2022
Publication Date Sep 1, 2022
Deposit Date Nov 18, 2022
Publicly Available Date Nov 18, 2022
Publisher Research Publications, Singapore
Pages 1385-1392
Book Title Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022)
ISBN 9789811851834
DOI https://doi.org/10.3850/978-981-18-5183-4_R22-24-242-cd
Keywords Asset management; Wind turbine blades; Petri nets; Structural health monitoring; Ultrasonic guided wave monitoring; Reliability of ultrasonic guided wave monitoring
Public URL https://nottingham-repository.worktribe.com/output/13753580
Publisher URL https://www.rpsonline.com.sg/proceedings/esrel2022/html/R22-24-242.xml
Related Public URLs https://www.esrel2022.com/

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