At the recent BIS Group 2nd Annual Wind Power Industry Big Data and Internet of Things Forum, LR's Dr Mark Spring delivered a paper on virtual sensors for condition monitoring covering:
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identification of risk-ranking for key failure modes
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derived health indices for most vulnerable components and sub-systems
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digital twin for every turbine, based on simulations based on turbine-specific data
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estimates of accumulated damage, remaining useful life and risk of failure based on combination of statistics, expert knowledge and physics of failure
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pilot project for operating wind farm (focus on frequency converter, gearbox and pitch system)
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new models embedded within computerised maintenance management system
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estimated cost-savings from reduced inspection, prioritised maintenance tasks, optimised inventory of spares and tools