| Summary: | In order to reduce the costs of wind energy, it is necessary to improve the wind turbine availability and reduce the operational and maintenance costs. The reliability and availability 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 wind industry currently uses lubrication oil analysis for detecting gearbox and bearing wear but cannot detect the functional failures of the lubrication oils. The main purpose of lubrication oil condition monitoring and degradation detection is to determine whether the oils have deteriorated to such a degree that they no longer fulfill their functions. This paper describes a research on developing online lubrication oil health condition monitoring and remaining useful life prediction with particle filtering technique using commercially available online sensors. The paper first presents a survey on current state-of-the-art online lubrication oil condition monitoring solutions and their characteristics along with the classification and evaluation of each technique. It is then followed by an investigation on wind turbine gearbox lubrication oil health condition monitoring and degradation detection using online viscosity and dielectric constant sensors. In particular, the lubricant performance evaluation and remaining useful life prediction of degraded lubrication oil with viscosity and dielectric constant data using particle filtering are presented. A simulation case study is provided to demonstrate the effectiveness of the developed technique.
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