Methods and systems for predicting risk of observable damage in wind turbine gearbox components

Abstract

Embodiments disclosed herein may include methods, systems, and tangible, non-transient, computer-readable media having instructions thereupon for determining a damage state of a wind turbine gearbox. A method performed, executed on a processor of a system, or implemented by a processor as instructions, may comprise producing a damage state diagnostic, producing a damage progression model for the wind turbine gearbox using operational data and a state transition function, and combining the damage state diagnostic with the damage progression model using a hybrid prognostics model to produce a probability distribution of a current damage state estimate. Producing the damage state diagnostic may comprise obtaining a measurement dataset for the wind turbine gearbox, integrating field-operator-provided intelligence into the measurement dataset, normalizing the measurement dataset with respect to a known failure behavior for the wind turbine gearbox, and combining the normalized measurement dataset with the known failure behavior to produce the damage state diagnostic.