Original paper

Deep digital twins for detection, diagnostics and prognostics

Volume: 140, Pages: 106612 - 106612
Published: Jun 1, 2020
Abstract
A generic framework for prognostics and health monitoring (PHM) which is rapidly deployable to heterogeneous fleets of assets would allow for the automation of predictive maintenance scheduling directly from operational data. Deep learning based PHM implementations provide part of the solution, but their main benefits are lost when predictions still rely on historical failure data and case-by-case feature engineering. We propose a solution to...
Paper Details
Title
Deep digital twins for detection, diagnostics and prognostics
Published Date
Jun 1, 2020
Volume
140
Pages
106612 - 106612
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