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

US11835030B2 · kind B2 · utility

Assignees

• Sentient Science Corporation · US
• Acciona Energia · ES

Inventors

• Vijayant Kumar · Andover, US
• Nathan Bolander · Idaho Falls, US
• Gunther Auer · Stockholm, SE
• Inigo Zalacain · Mutilva / Mutiloa, ES
• Mercedes Irujo · Pamplona, ES
• Enrique Iriarte · Sarriguren, ES

Key dates

• Filing date: Dec 31, 2019
• Grant date: Dec 5, 2023
• Expiry date: Jan 15, 2040

Classification

• Technology area (CPC Y): Emerging Cross-Sectional Technologies
• CPC primary: Y02E10/72
• WIPO field: Engines, pumps, turbines
• WIPO sector: Mechanical engineering

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.