Knowledge Driven Machine Learning Towards Interpretable Intelligent Prognostics and Health Management: Review and Case Study

Knowledge Driven Machine Learning Towards Interpretable Intelligent Prognostics and Health Management: Review and Case Study

Abstract Despite significant progress in the Prognostics and Health Management (PHM) domain using pattern learning systems from data, machine learning (ML) still faces challenges related to limited generalization and weak interpretability. A promising approach to overcoming these challenges is to em...

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Bibliographic Details
Main Authors: Ruqiang Yan, Zheng Zhou, Zuogang Shang, Zhiying Wang, Chenye Hu, Yasong Li, Yuangui Yang, Xuefeng Chen, Robert X. Gao
Format: Article
Language:English
Published: SpringerOpen 2025-01-01
Series:Chinese Journal of Mechanical Engineering
Subjects:
PHM
Knowledge driven machine learning
Signal processing
Physics informed
Interpretability
Online Access:https://doi.org/10.1186/s10033-024-01173-8
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https://doi.org/10.1186/s10033-024-01173-8

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