Scientific Machine Learning for Engine Health Management and Remaining Useful Life Prediction
Engine Health Management (EHM) depends on reliable forecasting of Remaining Useful Life (RUL) and on tracking thermal indicators such as turbine gas temperature (TGT). In practice, real-world fleet data are heterogeneous and non-stationary, and point predictions alone are insufficient for risk-aware maintenance decisions. This paper presents a multi-task scientific machine learning framework for turbine prognostics that jointly predicts turbine gas temperature untrimmed (TGTU), Delta Turbine Gas
Record details
Published: 28 May 2026
Source: arXiv
Category: Research
Topics: Privacy · Healthcare
Retrieved: 14 July 2026
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ethics.ai (28 May 2026), “Scientific Machine Learning for Engine Health Management and Remaining Useful Life Prediction,” evidence record 3477, https://ethics.ai/record/3477 (originally published by arXiv).
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