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Deep Learning Based Defect Detection for Solder Joints on Industrial X-Ray Circuit Board Images

Published:

May 6, 2021

Author:

Qianru Zhang, Meng Zhang, Chinthaka Gamanayakey, Chau Yueny, Zehao Gengz, Hirunima Jayasekaray, Xuewen Zhangz, Chia-wei Woox, Jenny Lowx, Xiang Liuz

Abstract:

Quality control is of vital importance during electronics production. As the methods of producing electronic circuits improve, there is an increasing chance of solder defects during assembling the printed circuit board (PCB). Many technologies have been incorporated for inspecting failed soldering, such as X-ray imaging, optical imaging, and thermal imaging. With some advanced algorithms, the new technologies are expected to control the production quality based on the digital images. However, current algorithms sometimes are not accurate enough to meet the quality control. Specialists are needed to do a follow-up checking. For automated X-ray inspection, joint of interest on the X-ray image is located by region of interest (ROI) and inspected by some algorithms. Some incorrect ROIs deteriorate the inspection algorithm....

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Company Information:

Southeast University (SEU)

Southeast University is one of only 32 universities directly administered by the Chinese Department of Education, which are considered the top class universities in China.

Nanjing, China

School

  • Phone 0086-25-83793022
  • Fax 0086-25-83792737

Southeast University (SEU) website

Company Postings:

(2) technical library articles

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  • Dec 07, 2020 - A Non-destructive Approach to Identify Intermittent Failure Locations on Printed Circuit Cards (PCC) that have been Temperature Cycle Tested | ACI Technologies, Inc.
  • Dec 02, 2020 - SMT007-MIRTEC Intelligent Factory Automation Article-November 2020 | MIRTEC Corp
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