A hybrid physics-informed neural network for main bearing fatigue prognosis under grease quality variation

Author:

Yucesan Yigit A.ORCID,Viana Felipe A.C.ORCID

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference42 articles.

1. United States wind turbine database;Hoen,2018

2. A feasibility study into prognostics for the main bearing of a wind turbine;Butler,2012

3. Micro-siting of wind turbine in complex terrain: simplified fatigue life prediction of main bearing in direct drive wind turbines;Watanabe;Wind Eng.,2015

4. ISO 281, Rolling Bearings – Dynamic Load Ratings and Rating Life,2007

5. A methodology for reliability assessment and prognosis of bearing axial cracking in wind turbine gearboxes;Guo;Renew. Sustain. Energy Rev.,2020

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