Design of high frequency transformer inner glue defect detection system based on vision

Feifei Liu; Lele Cao; Yuanmin Tu; Xinyu Chen

doi:10.1117/12.2656563

20 October 2022 Design of high frequency transformer inner glue defect detection system based on vision

Feifei Liu, Lele Cao, Yuanmin Tu, Xinyu Chen

Proceedings Volume 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022); 124510L (2022) https://doi.org/10.1117/12.2656563
Event: 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 2022, Chongqing, China

Abstract

Aiming at the problems of low efficiency, high labor intensity and poor real time of manual detection of inner glue defects in high frequency transformers, and the difficulty of traditional detection algorithms to quickly and accurately detect the defects of high frequency transformer images with low contrast and strong reflection, a high frequency transformer inner glue defect detection system is designed to achieve the purpose of automatic and rapid detection of workpieces. The hardware side of the system uses CMOS camera and LED low-angle ring light source by analyzing the workpiece structure and the image characteristics of the defect area. The software first uses VisionPro vision software to design the image pre-processing program to locate and crop the original image to obtain the image of the inner glue area, then uses VisionPro Deep Learning software to build the defect detection model, and finally integrates the image preprocessing program and the detection model and designs the upper computer operation interface. The experimental results show that the detection accuracy of the system is 99%, and the average detection time per image is 46.7ms, which can quickly and accurately detect the defects of inner glue of high frequency transformers and meet the requirements of real-time inspection of factory products.

Citation Download Citation

Feifei Liu, Lele Cao, Yuanmin Tu, and Xinyu Chen "Design of high frequency transformer inner glue defect detection system based on vision", Proc. SPIE 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 124510L (20 October 2022); https://doi.org/10.1117/12.2656563

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KEYWORDS

Defect detection

Transformers

Visual process modeling

Data modeling

Inspection

Cameras

Imaging systems

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