Aiming at the disadvantages of traditional manual identification method of chip welding cavity X-ray inspection, such as high technical threshold, strong subjectivity of inspection results and long inspection time, an automatic identification method based on digital image processing is proposed in this paper. Through histogram equalization, denoising, image enhancement and threshold segmentation on X-ray images containing welding cavity defects, welding cavity defects can be identified quickly and accurately, and the welding cavity rate of products can be calculated, which improves the efficiency and accuracy of inspection test.
Based on the requirements of intelligent transformation in electronic component manufacturing enterprises, this paper focuses on the application of artificial intelligence technology in the field of electronic component manufacturing based on the analysis of the connotation of intelligent manufacturing. The application status of four key technologies of machine vision, information system, Internet of Things (IOT) and big data in quality detection, manufacturing informationization, interactive perception and decision analysis is studied, and the existing problems are analysed. Finally, the future development trend of intelligent manufacturing of electronic components is prospected, which can provide reference for intelligent manufacturing research.
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