Work

Remaining useful life prediction of bearings under steady and varying operating conditions using digital twin-based deep learning

Year: 2024

Type: conference-paper

Abstract: status: Published online

Source: Lirias

Authors: Hosseinli, Ali, Ooijevaar, Ted, Gryllias, Konstantinos

Institutions: Flanders Make (Belgium), KU Leuven

Language: English

Topic: Machine Fault Diagnosis Techniques

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

Funders: Vlaams Supercomputer Centrum, Flanders Make, KU Leuven, Vlaamse regering

OpenAlex ID: W6986915106

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