arXiv Machine Learning By Ahmad BahooToroody, Oleksiy Bondarenko, Mohammad Mahdi Abaei, Niki Yoichi, Enrico Zio

Marine Engine Fault Dataset: Open-Access Data under Controlled Reference and Fault Scenario Conditions

Read the original on arXiv Machine Learning →

arXiv:2607. 19444v1 Announce Type: new Abstract: Open-access datasets for marine-engine predictive maintenance remain scarce, particularly those from controlled fault experiments with documented operating conditions, subsystem-level interventions and system-level measurements.

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arXiv Machine Learning
Jul 21

Leakage-Robust Evaluation and Data-Scale Sensitivity of Attention-Enhanced Multi-Task Learning for Joint Fault Diagnosis and Remaining Useful Life Estimation

arXiv:2607. 16493v1 Announce Type: new Abstract: Multi-task deep learning models that jointly perform fault classification and remaining useful life (RUL) regression are increasingly used in predictive maintenance, yet reported performance can be strongly affected by how sliding-window sequences are split into training and test sets.

By Md Mahamudur Rahaman Shamim, Md. Nuruzzaman, Zannatul Ferdus, Md Rajib Ahmed, Abieer Nwshad Anward, Mohammad Tooneer, Johir Uddin Khan, Khalid Hossen