Online condition monitoring and remaining useful life prediction of particle contaminated lubrication oil

Abstract

To increase wind energy production rate, there is a pressing need to improve the wind turbine availability and reduce the operational and maintenance costs. The safety and reliability of a functioning wind turbine depend largely on the protective properties of the lubrication oil for its drive train subassemblies such as gearbox and means for lubrication oil condition monitoring and degradation detection. The purpose of lubrication oil condition monitoring and degradation detection is to determine whether the oil has deteriorated to such a degree that it no longer fulfills its function. In this paper, particle contamination of lubrication oil and the remaining useful life (RUL) of the particle contaminated lubrication oil are investigated. Physical models are developed to quantify the relationship between particle contamination level and the outputs of commercially available online oil dielectric and viscosity sensors. The effectiveness of the developed models is then validated using laboratory experiments. In particular, the remaining useful life prediction of degraded lubrication oil with viscosity and dielectric constant data using particle filtering is presented. A simulation case study is provided to demonstrate the effectiveness of the developed technique.