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VACUUM ›› 2025, Vol. 62 ›› Issue (5): 44-52.doi: 10.13385/j.cnki.vacuum.2025.05.07

• Thin Film • Previous Articles     Next Articles

Surface Defect Detection Method of Spacecraft Flexible Thermal Control Coating Driven by Multidimensional Attention Mechanism

NI Jun1,2, GUO Teng1,2, LI Canlun1,2, HE Hengyang3, LI Rongyi3   

  1. 1. Shanghai Institute of Spacecraft Equipment, Shanghai 200240, China;
    2. Shanghai Aerospace Yuda Technology Co., Ltd., Shanghai 200240, China;
    3. Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, China
  • Received:2024-12-02 Published:2025-09-29

Abstract: Flexible thermal control coatings are applied to the outer surface of spacecraft to control the thermal balance of the spacecraft surface based on their own thermo-physical properties. During the magnetron sputtering process, process instability often leads to various defects in the coating, which in turn affects the coating quality. Traditional magnetron sputtering coating defect detection requires shutdown for inspection, which is inefficient and does not respond in a timely manner. This paper proposes a deep learning algorithm for image detection driven by a multi-dimensional attention mechanism, constructing a correlation mapping model between monitoring data, detection image sensitive features, and coating defects, to achieve efficient and high-accuracy intelligent identification. The experimental verification shows that the model recognition accuracy for cracks, electric sparks, and underplating defects is above 96%, laying a solid foundation for the online detection of flexible thermal control coatings on spacecrafts.

Key words: thermal control coating, magnetron sputtering, multi-dimensional attention mechanism, intelligent identification

CLC Number:  TB43

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