Estimation of Remaining Useful Life of a Fatigue Damaged Wind Turbine Blade with Particle Filters
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-74421-6_42
Reference48 articles.
1. Wymore, M.L., Van Dam, J.E., Ceylan, H., Qiao, D.: A survey of health monitoring systems for wind turbines. Renew. Sust. Energ. Rev. 52(1069283), 976–990 (2015)
2. Griffin, D.A., Malkin, M.C.: I Introduction, Principal Engineer, Turbine Engineering Group, Senior Engineer, Press Release, Suzlon Energy Unlimited.: Lessons learned from recent blade failures: primary causes and risk-reducing technologies. In: 49th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition, Jan 2011, pp. 1–9
3. El-Thalji, I., Jantunen, E.: On the development of condition based maintenance strategy for offshore wind farm: requirement elicitation process. Energy Proc. 24, 328–339 (2012)
4. Gupta, A., Lawsirirat, C.: Strategically optimum maintenance of monitoring-enabled multi-component systems using continuous-time jump deterioration models. J. Qual. Maint. Eng. 12(3), 306–329 (2006)
5. Campos, J.: Development in the application of ICT in condition monitoring and maintenance. Comput. Ind. 60(1), 1–20 (2009)
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