Bayesian approach with subjective opinion fusions for wind turbine maintenance

An optimal Bayesian update strategy that implements the subjective opinions of several experts are introduced for preventive maintenance of wind turbines while single expert opinion has been introduced by the author in the previous studies. This work is introducing the opinion of the wind farm manager or technician via subjective opinions based on a Bayesian adaptive update strategies for optimal preventive maintenance. Subjective opinion will be implemented to Bayesian cycles while experts can impact the distribution parameters with no knowledge of statistics but just by presenting their opinion as belief, disbelief or uncertainty. Statistical parameters such as minimal time of maintenance and cost of new strategy will be impacted by the interaction of wind farm manager and technician that interact with quantitative data with their opinions. The approach employs and complements the quantitative data from turbine Supervisory control and data acquisition (SCADA).