Automated Visual Inspection for Solder Joints of PCB Based on 3-D Image Analysis | Zendy

Toshifumi Honda | Zendy; Hisae Yamamura | Zendy; M. Nomoto | Zendy; Takanori Ninomiya | Zendy; Tomoharu Horii | Zendy; Yoshio MIYAWAKI | Zendy

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Automated Visual Inspection for Solder Joints of PCB Based on 3-D Image Analysis

Author(s) -

Toshifumi Honda,

Hisae Yamamura,

M. Nomoto,

Takanori Ninomiya,

Tomoharu Horii,

Yoshio MIYAWAKI

Publication year - 1999

Publication title -

journal of robotics and mechatronics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.257

H-Index - 19

eISSN - 1883-8049

pISSN - 0915-3942

DOI - 10.20965/jrm.1999.p0104

Subject(s) - automated optical inspection , soldering , fillet (mechanics) , artificial intelligence , printed circuit board , visual inspection , joint (building) , automated x ray inspection , computer vision , computer science , inspection time , laser scanning , specular reflection , image processing , laser , materials science , optics , engineering , image (mathematics) , structural engineering , psychology , developmental psychology , physics , composite material , operating system

Automated visual solder inspection was studied for different printed circuit boards (PCBs) based on 3-D-image analysis. The optical 3-D scanner accurately detects height of a solder joint from differently focused images of a laser spot. Emitted laser light on the solder joint is detected simultaneously by plural sensors whose focal points are set at different height to realize high-speed height acquisition without secondary-reflection problems caused by the specular surface of the solder joint. An inspection algorithm was designed to recognize a solder joint using detected height and the intensity image so that different shapes of solder fillet do not affect inspection performance. A solder joint is classified based on extracted 3-D features of its fillet shape and 3-D location of the lead from its pad. Inspection parameters are automatically generated with inspection parameter autogeneration using electronic component and PCB design data. Evaluation showed the system gave 100% defect detection and very few false alarms (0.13%) using autogenerated inspection parameters. Results show the technique to be promising in actual production lines for different PCBs.

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