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Proceedings Paper

Fourier series analysis for in-process inspection of XFP SMT solder joints
Author(s): David Zhengwen Zhang; Jia-Chang Wang; Ching Lee
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Paper Abstract

With the increased use of extra-fine-pitch (XFP) surface mounted components in electronic products, machine vision techniques for in-process inspection of solder joints during PCB assembly have become highly demanding. Existing algorithms for this purpose are mostly designed to perform inspection based on the analysis of 3D image profiles of individual solder joints. They are computation intensive and often result in expensive implementations. This work introduces a new approach solder joint inspection. With this approach, the inspection problem is considered as a task of detection textural distortions for the 2D proper-view images of a printed circuit board. A real-time texture inspection algorithm based on Fourier Series Analysis is developed to carry out the inspection. The algorithm has been implemented and tested on a PC-based vision system. The results from the tests show that the proposed technique can perform practical PCB inspection successfully. This suggest that real-time and in-process inspection of XFP solder joints may be carried out by a low cost PC-based vision system. In this paper, the principles of Fourier Series Analysis are discussed and the proposed algorithm described. The usefulness of the algorithm in texture inspection in general, and PCB inspection in particular is investigated. The performances of the proposed technique are demonstrated on practical PCB inspection problems.

Paper Details

Date Published: 17 December 1998
PDF: 10 pages
Proc. SPIE 3518, Sensors and Controls for Intelligent Machining, Agile Manufacturing, and Mechatronics, (17 December 1998); doi: 10.1117/12.332800
Show Author Affiliations
David Zhengwen Zhang, Univ. of Liverpool (United Kingdom)
Jia-Chang Wang, Univ. of Liverpool (United Kingdom)
Ching Lee, Univ. of Liverpool (United States)


Published in SPIE Proceedings Vol. 3518:
Sensors and Controls for Intelligent Machining, Agile Manufacturing, and Mechatronics
Patrick F. Muir; Patrick F. Muir; Peter E. Orban, Editor(s)

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