Research on the new generation framework of PHM systems for railway trains
Scientific maintenance of operating vehicles and ensuring the safety of train operations have always been the core issues in the field of rail transit. In recent years, with the major demands of predictive maintenance and unmanned driving, there is an urgent need to realize the PHM (prognostics and...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Electric Drive for Locomotives
2024-01-01
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| Series: | 机车电传动 |
| Subjects: | |
| Online Access: | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2024.01.001 |
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| Summary: | Scientific maintenance of operating vehicles and ensuring the safety of train operations have always been the core issues in the field of rail transit. In recent years, with the major demands of predictive maintenance and unmanned driving, there is an urgent need to realize the PHM (prognostics and health management) functions of holographic state perception, elaborate diagnosis and prediction, and timely feedback and disposal for railway trains. The existing system frameworks suffer from perception inefficiency, insufficient fusion, poor model optimization dynamics, weak computational synergy, and low levels of autonomous decision-making, etc. The development of advanced IoT, big data, artificial intelligence, digital twins, and other technologies has pushed the PHM system frameworks of railway trains to evolve to a higher level of intelligence. In this paper, the technical development stage of PHM systems of railway trains is reviewed and categorized. Furthermore, the PHM 4.0 framework for railway systems, which leverages ubiquitous sensing and collaborative computing, has been introduced. This framework is described in detail, elucidating its foundational principles, system structure, and key technologies. The paper also outlines the approaches, techniques, and anticipated outcomes associated with the deep integration of ubiquitous sensing, collaborative computing, and health management. Additionally, it clarifies the primary focus of current technological research, supporting enhanced safety and maintenance quality in railway operations. |
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| ISSN: | 1000-128X |