Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Automatic detection method for BGA defects based on x-ray imaging

Not Accessible

Your library or personal account may give you access

Abstract

Ball grid array (BGA) packaging is a high-density surface mount technology with the advantages of small size, good heat dissipation, and electrical properties, and is widely applied in the production of large-scale integrated circuits. With the rapid development of IC integration, devices assembled using BGA technology generally have greater complexity. However, BGA defects can seriously affect device performance and bring difficulties to product quality inspection. More importantly, in the process of BGA defect inspection, the high complexity of the device brings unprecedented challenges to the precise location of defects, which means that corresponding inspection methods should be improved. To this end, this paper proposes an automatic detection method for BGA defects based on x-ray imaging. First, x-ray imaging technology is utilized to achieve non-destructive detection of the BGA area inside the device and generate image data. On this basis, a set of algorithms including threshold separation, detection filling, and closing operation is designed to complete automatic detection of BGA defects. Furthermore, to objectively evaluate the effectiveness and performance of the proposed method, we conduct a series of comparative experiments using simulated and real data, and generate visual outputs. Through these experiments and analyses, we confirm that the proposed method plays an active and effective role and has robust performance in BGA defect detection. In particular, our method shows the expected performance in precisely finding BGA edge defects and subtle defects.

© 2022 Optica Publishing Group

Full Article  |  PDF Article
More Like This
Lightweight prohibited item detection method based on YOLOV4 for x-ray security inspection

Dongming Liu, Jianchang Liu, Peixin Yuan, and Feng Yu
Appl. Opt. 61(28) 8454-8461 (2022)

Improved YOLOX detection algorithm for contraband in X-ray images

Yinsheng Zhang, Wenxiao Xu, Shanshan Yang, Yongjie Xu, and Xinyuan Yu
Appl. Opt. 61(21) 6297-6310 (2022)

Automatic accurate longitudinal location of structural defects in sewer pipes via monocular ranging

Jianghai He, Zhiqun Hou, Daming Zhu, Zhaoyong Li, and Ziqian Li
Appl. Opt. 61(27) 7899-7911 (2022)

Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (11)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Tables (2)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (8)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.