
핵추진잠수함 도입에 따른 해양 전자시스템의 통합 열관리 및 건전성관리 프레임워크 연구
Ⓒ 2026 Korea Society for Naval Science & Technology
초록
첨단 해양 플랫폼의 전자시스템이 고집적·복잡화됨에 따라 열관리와 시스템 건전성 관리의 통합 필요성이 증가하고 있다. 본 연구는 열관리, 예측 및 건전성 관리(PHM), 상태기반정비 관련 연구를 분석하여 데이터, 통합, 의사결정 및 검증 측면의 연구 공백을 도출하였다. 이를 바탕으로 열정보를 전력, 진동, 계산부하 및 환경조건 등 다중 상태정보와 연계하여 상태평가와 유지보수를 지원하는 미션 전자 열 관리 아키텍처(METMA)를 제안하였다. 또한 TEVV 벤치와 비민감 데이터를 활용한 단계적 검증체계를 제시하여 향후 해양 전자시스템의 통합 열관리 및 건전성 관리 실증연구를 위한 기반을 마련하였다.
Abstract
As electronic systems in advanced maritime platforms become increasingly integrated and complex, the need for integrated thermal management and system health management continues to grow. This study reviews research on thermal management, prognostics and health management, and condition-based maintenance, identifying research gaps in data, integration, decision-making, and verification. Based on these findings, the Mission Electronics Thermal Management Architecture is proposed to support condition assessment and maintenance by integrating thermal information with multimodal condition data, including power, vibration, computational load, and environmental conditions. A phased verification framework using a TEVV bench and non-sensitive data is presented as a foundation for future empirical research on integrated thermal and health management of maritime electronic systems.
Keywords:
Thermal Management, METMA, Mission Electronics Thermal Management Architecture, PHM, Prognostics and Health Management, CBM+, Condition-Based Maintenance Plus, TEVV, Test, Evaluation, Verification & Validation키워드:
열관리, 임무전자 열관리 아키텍처, 고장예지 및 건전성 관리, 확장형 상태기반정비, 시험·평가·검증·확인References
- N. Vichare & M. Pecht, ‘Enabling Electronic Prognostics Using Thermal Data,’ in Proceedings of the 12th International Workshop on Thermal Investigation of ICs and Systems, 2006.
- Michael G. Pecht, Prognostics and Health Management of Electronics, John Wiley & Sons, 2008.
-
Ying Peng, Ming Dong, & Ming Jian Zuo, ‘Current Status of Machine Prognostics in Condition-Based Maintenance: A Review,’ The International Journal of Advanced Manufacturing Technology, VOL. 50, 2010, pp. 297-313.
[https://doi.org/10.1007/s00170-009-2482-0]
-
Andrew K. S. Jardine, Daming Lin, & Dragan Banjevic, ‘A Review on Machinery Diagnostics and Prognostics Implementing Condition-Based Maintenance,’ Mechanical Systems and Signal Processing, VOL. 20, NO. 7, 2006, pp. 1483-1510.
[https://doi.org/10.1016/j.ymssp.2005.09.012]
- IEEE, IEEE Std 1856-2017: IEEE Standard Framework for Prognostics and Health Management of Electronic Systems, 2017.
- ISO, ISO 13381-1:2025, Condition Monitoring and Diagnostics of Machine Systems—Prognostics—Part 1: General Guidelines and Requirements, 2025.
-
Peng Zhang, Zeyu Gao, Lele Cao, Fangyang Dong, Yongjiu Zou, Kai Wang, Yuewen Zhang, & Peiting Sun, ‘Marine Systems and Equipment Prognostics and Health Management: A Systematic Review from Health Condition Monitoring to Maintenance Strategy,’ Machines, VOL. 10, NO. 2, 2022, Article 72.
[https://doi.org/10.3390/machines10020072]
- ISO, ISO 13374-2:2007, Condition Monitoring and Diagnostics of Machines—Data Processing, Communication and Presentation—Part 2: Data Processing, 2007.
- MIMOSA, Open System Architecture for Condition-Based Maintenance (OSA-CBM), Version 3.3.1, MIMOSA, 2010.
- Steven R. Hirshorn, Linda D. Voss, & Linda K. Bromley, NASA Systems Engineering Handbook, NASA/SP-2016-6105 Rev. 2, National Aeronautics and Space Administration, 2016.
-
Chun Fui Liew, Gengyu Li, Akira Osaka, Samir Khan, Naoya Takeishi, & Takehisa Yairi, ‘Development and Sharing of a Multi-Modal Indoor UAV Dataset for PHM Research,’ Proceedings of the Asia Pacific Conference of the PHM Society 2025, VOL. 5, NO. 1, 2025.
[https://doi.org/10.36001/phmap.2025.v5i1.4701]