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Machine Learning based Data Driven Diagnostic and Prognostic Approach for Laser Reliability Enhancement

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arxiv 2203.11728 v1 pith:UUUO6KWV submitted 2022-03-19 eess.SP cs.LG

Khouloud Abdelli , Helmut Griesser , Stephan Pachnicke This is my paper · ORCID
classification eess.SPcs.LG
keywords laserapproachdatadiagnosticlearningmachineprognosticproposed
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In this paper, a data-driven diagnostic and prognostic approach based on machine learning is proposed to detect laser failure modes and to predict the remaining useful life (RUL) of a laser during its operation. We present an architecture of the proposed cognitive predictive maintenance framework and demonstrate its effectiveness using synthetic data.

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