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Deep Learning Based Surface Defect Detection Method of Flexible Solar Array Hinge |
WANG Bing, PI Gang, CHEN Wencheng, XIE Haifeng, SHI Xiangling |
Shanghai Aerospace Equipment Manufacturing Co. Ltd, Shanghai 200245, China |
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Abstract In order to improve the detection accuracy and efficiency of flexible solar array hinge defect detection, a two-stage algorithm combining target detection and classification network is proposed by carrying out the research on the surface defect detection method of flexible solar array hinge based on deep learning. The method adopts an automatic camera device to take photos of the hinges and record the surface state of hinges. At the same time, transfer learning and data enhancement algorithms are introduced to solve the problem of lack of defect samples. At the same time, the requirements for computing resources are low and the computational performance is high, so as to achieve the effect of high accuracy and efficiency of surface defect detection.
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Received: 09 June 2022
Published: 31 March 2023
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