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논문 기본 정보

자료유형
학술저널
저자정보
Kwang-Seong Shin (Sunchon National University) Jong-Chan Kim (Sunchon National University) Seong-Yoon Shin (Kunsan National University)
저널정보
한국정보통신학회JICCE Journal of information and communication convergence engineering Journal of information and communication convergence engineering Vol.22 No.2
발행연도
2024.6
수록면
159 - 164 (6page)

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초록· 키워드

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This study aimed to develop an advanced anomaly-detection system tailored for solar power distribution panels using thermal imaging cameras to ensure operational stability. It addresses the imperative shift toward digitalized safety management in electrical facilities, transcending the limitations of conventional empirical methodologies. Our proposed system leverages a faster R-CNN-based artificial intelligence model optimized through meticulous hyperparameter tuning to efficiently detect anomalies in distribution panels. Through comprehensive experimentation, we validated the efficacy of the system in accurately identifying anomalies, thereby propelling safety protocols forward during the fourth industrial revolution. This study signifies a significant stride toward fortifying the integrity and resilience of solar power distribution systems, which is pivotal for adapting to emerging technological paradigms and evolving safety standards in the energy sector. These findings offer valuable insights for enhancing the reliability and efficiency of safety management practices and fostering a safer and more sustainable energy landscape.

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Abstract
I. INTRODUCTION
II. RELATED WORKS
III. SYSTEM MODEL AND METHODS
IV. RESULTS AND DISCUSSIONS
V. CONCLUSIONS
REFERENCES

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