An asset management modelling framework for wind turbine blades considering monitoring system reliability

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

Abstract

By incorporating information about asset condition from a monitoring system, engineers can utilize asset management models to manage maintenance activities on wind turbine blades throughout their lifespan. This can lower operating and maintenance costs and increase the life of the blades. The asset management model relies on the monitoring system as a source of information, however, commonly the reliability of the monitoring system is not considered. This paper presents a wind turbine blade asset management Petri net (PN) model that covers the blade asset management process, including degradation, inspection, condition monitoring (CM), and maintenance processes. The paper proposes two contributions. Firstly, while taking into account detailed industry guidelines, the developed model can forecast the future blade condition for a given asset management strategy. Secondly, it investigates the impact of the reliability of the monitoring system on the asset management modelling results. With the aid of the developed model, the number of repair actions and probability distributions of blade condition discovery time are obtained. In addition, the PN gives an indication of how misreporting (underestimation and overestimation) occurs and the extent of the misreporting. The simulation results illustrate the degree of uncertainty introduced into the monitoring results by the reliability of the monitoring system and, consequently, the extent to which this factor influences the maintenance strategies. The proposed model can be used to support asset management decisions when monitoring system performance degrades.

Citation

Wu, W., Prescott, D., Remenyte-Prescott, R., Saleh, A., & Chiachio Ruano, M. (2024). An asset management modelling framework for wind turbine blades considering monitoring system reliability. Reliability Engineering and System Safety, 252, Article 110478. https://doi.org/10.1016/j.ress.2024.110478

• Journal Article Type: Article
• Acceptance Date: Aug 29, 2024
• Online Publication Date: Sep 4, 2024
• Publication Date: 2024-12
• Deposit Date: Sep 5, 2024
• Publicly Available Date: Sep 5, 2024
• Journal: Reliability Engineering & System Safety
• Print ISSN: 0951-8320
• Electronic ISSN: 1879-0836
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 252
• Article Number: 110478
• DOI: https://doi.org/10.1016/j.ress.2024.110478
• Keywords: Asset management; Wind turbine blades; Petri nets; Structural health monitoring; Monitoring system reliability
• Public URL: https://nottingham-repository.worktribe.com/output/39171889
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0951832024005507#