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The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the Physical Activity for Health Group based within the School of Psychological Sciences & Health. Research here seeks to better understand how and why physical activity improves health, gain a better understanding of the amount, intensity, and type of physical activity needed for health benefits, and evaluate the effect of interventions to promote physical activity.

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Condition based maintenance for offshore wind turbines : the effects of false alarms from condition monitoring systems

May, Allan and McMillan, David (2013) Condition based maintenance for offshore wind turbines : the effects of false alarms from condition monitoring systems. In: Safety, Reliability and Risk Analysis: Beyond the Horizon. CRC Press, pp. 783-789. ISBN 9781138001237

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As wind turbines increase in size and move offshore, operations and maintenance procedures need to be optimised to increase reliability, safety and maximise cost effectiveness. The practice of installing condition monitoring systems to allow the real time monitoring of assets as a means to achieve these goals is becoming more wide-spread. This allows operators to adopt a condition based maintenance approach that theoretically allows reduced costs over both preventive and corrective maintenance strategies. There have been several studies into the possible benefits and cost advantages of using a condition based maintenance strategy. However, few have examined the implications of system detection rates or false alarms. Many studies have assumed that condition monitoring systems will detect all the faults they are designed to observe. This will not be the case. Investigating false alarms or ignoring false positives in a remote offshore environment will incur costs that may alter the cost benefit of condition monitoring systems. Probabilistic models are used in the paper to determine the possible benefits of using condition monitoring systems and the effect that system detection rates and false positives have on the reliability of the system. The methods used include Markov chains and time-series modelling. © 2014 Taylor & Francis Group, London..