A Computational Framework for Life-Cycle Management of Wind Turbines incorporating Structural Health Monitoring

Long-term efficiency and life-cycle costs of wind turbines are the most critical problems for owners and operators. The integration of structural health monitoring into life-cycle management strategies facilitates a reliable, efficient operation of wind turbines and can help reducing the life-cycle costs significantly. This paper presents a life-cycle management (LCM) framework for online monitoring and performance assessment of wind turbines, enabling optimum maintenance and inspection planning at minimum associated life-cycle costs. Incorporating continuously updated monitoring data – i.e. structural, environmental and operational data – the framework allows capturing and understanding the actual wind turbine condition and, hence, reduces uncertainty in structural responses as well as load effects acting on the structure. As will be shown in this paper, the framework integrates a variety of heterogeneous hardware and software components, including sensors and data acquisition units, server systems, Internet-enabled user interfaces as well as finite element models for system identification, and a multi-agent system for self-detecting sensor malfunctions. To K. Smarsly, D. Hartmann and K. H. Law 2/44 validate its capabilities and to demonstrate its practicability, the framework is deployed for continuous monitoring and life-cycle management of a 500 kW wind turbine. Remote lifecycle analyses of the monitored wind turbine are conducted and case studies are presented investigating both the structural performance and the operational efficiency of the wind turbine.