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Related Concept Videos

X-ray Imaging01:24

X-ray Imaging

5.9K
German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
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Related Experiment Video

Updated: Aug 25, 2025

Comprehensive Characterization of Extended Defects in Semiconductor Materials by a Scanning Electron Microscope
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Automatic detection method for BGA defects based on x-ray imaging.

Kai Xiao, Qin Li, Yang Chen

    Applied Optics
    |October 18, 2022
    PubMed
    Summary

    This study introduces an automated X-ray imaging method for detecting Ball Grid Array (BGA) defects in complex integrated circuits. The novel approach effectively identifies subtle and edge defects, improving quality inspection.

    Area of Science:

    • Materials Science
    • Electrical Engineering
    • Computer Vision

    Background:

    • Ball Grid Array (BGA) packaging is crucial for high-density integrated circuits.
    • Increasing IC complexity poses challenges for BGA defect inspection and precise defect localization.
    • Existing inspection methods struggle with the intricate nature of modern BGA devices.

    Purpose of the Study:

    • To develop an automated detection method for Ball Grid Array (BGA) defects using X-ray imaging.
    • To address the challenges in precise defect localization within complex BGA assemblies.
    • To enhance the accuracy and efficiency of quality inspection for BGA packaging.

    Main Methods:

    • Utilized X-ray imaging for non-destructive detection of BGA areas.
    • Developed a defect detection algorithm incorporating threshold separation, detection filling, and closing operations.

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  • Conducted comparative experiments with simulated and real data for validation.
  • Main Results:

    • The proposed method achieved automatic detection of BGA defects.
    • Experimental results demonstrated the method's effectiveness and robust performance.
    • The approach showed particular success in precisely identifying BGA edge and subtle defects.

    Conclusions:

    • The developed X-ray imaging-based method is an effective solution for automatic BGA defect detection.
    • The algorithm successfully addresses the challenges of precise defect localization in complex devices.
    • This technique offers a significant improvement for quality inspection in BGA packaging.