BGA Solder Void Detection via Multi-Threshold X-Ray Binarization
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Solution Overview
Problem
Accurate detection and characterization of voids in BGA solder balls are challenging due to their hidden nature beneath the surface, making visual inspection impossible and requiring X-ray imaging, which faces difficulties in small contrast, non-uniform grayscale intensity, and unknown geometry.
Innovation Solution
A method involving binarization of X-ray images at multiple thresholds to generate multiple binarized images, extracting and combining information to detect irregularities or defects, estimating the non-defective object, and identifying voids through a convex envelope and accumulator array analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If X-ray imaging is used to detect voids in solder balls, then detection capability is improved, but image quality deteriorates due to small contrast and non-uniform grayscale intensity
Solution Approach 1:
The patent segments the image analysis process by binarizing the X-ray image at multiple different thresholds to generate multiple binarized images. Each binarized image highlights different contrast ranges, allowing the system to segment the detection task into multiple sub-tasks that can be processed independently and then combined, thereby overcoming the limitation of single-threshold binarization in handling non-uniform grayscale intensity.
Solution Approach 2:
The patent introduces a new dimension to the analysis by creating multiple binarized images from a single X-ray image through varying threshold values. This transforms the two-dimensional grayscale image into multiple binary images that represent different contrast levels, enabling comprehensive void detection across various intensity ranges that would be invisible in a single-threshold approach.
2Measurement precision
If multiple binarization thresholds are used to enhance void detection, then detection accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent segments the detection process into multiple independent binarization steps, each operating on the same X-ray image but with different thresholds. This segmentation allows parallel processing and simplifies the overall algorithm by breaking down the complex task of detecting voids in non-uniform grayscale images into multiple simpler binary image generation steps that can be efficiently processed and combined.
Solution Approach 2:
The patent merges the results from multiple binarized images by combining the information extracted from each binary image. This merging process integrates the advantages of multiple threshold analyses into a unified void detection result, achieving high detection accuracy while managing processing complexity through systematic combination of intermediate results.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively detects and characterizes voids in BGA solder balls by enhancing the detection of voids' characteristics such as position, diameter, and volume, improving the reliability of solder joints by providing comprehensive information from multiple binarized images.
Implementation Method 1
X-ray imaging may be used to inspect solder balls for voids
Data Source
AI summary
A method for the detection of an irregularity in an object based on an image of the object that includes the steps of binarizing the image at a plurality of binarization thresholds to obtain a plurality of binarized images, extracting information from each of the binarized images, estimating the regular object resulting from the binarization at the respective binarization threshold of an image of a version of the object in which the irregularity is absent, combining the information extracted from each of the binarized images, and detecting the irregularity based on the combined information. A method for the detection of a defect in a solder element based on an X-ray image of the solder element. This aspect includes the steps of binarizing the image at a plurality of binarization thresholds to obtain a plurality of binarized images, extracting information from each of the binarized images, combining the information extracted from each of the binarized images, and detecting the defect based on the combined information.