Online particle-contaminated lubrication oil condition monitoring and remaining useful life prediction for wind turbines

The widespread deployment of industrial wind projects will require a more proactive maintenance strategy in order to be more cost competitive. This paper describes an ongoing research project on developing online lubrication oil condition monitoring and degradation detection tools using commercially available online sensors. In particular, an investigation on particle contamination of lubrication oil is reported. Methods are presented for online lubrication oil condition monitoring and remaining useful life prediction using viscosity and dielectric constant sensors along with particle filtering technique. Physical models are derived in order to establish the mathematical relationship between lubrication oil degradation and particle contamination level. Laboratory experiments are performed to validate the accuracy of the developed models by comparing viscosity and dielectric constant sensor outputs of different particle concentration levels with those simulated by the lubricant deterioration physical models. A case study on lubrication oil degradation detection and remaining useful life prediction is provided. Discussions on the potential for extrapolating the presented methods to typical wind turbine gearbox oil and the practical implementation of particle filter-based approach for online wind turbine gearbox oil remaining useful life prediction are also included. Copyright (c) 2014 John Wiley & Sons, Ltd.