A novel solder joint diagnosis algorithm using differential geometry approach in high-density flexible integrated circuit substrates. (6th May 2021)

• Record Type: Journal Article
• Authors: Zeng, Yong; Hu, Yueming; Huang, Dan
• Is Part Of: Measurement science & technology. Volume 32:Number 7(2021)
• Publication Date: 2021-05-06
• Subjects: flexible integrated circuit substrates -- defect diagnosis -- features extraction -- differential geometry -- solder joint -- vision inspection; Physical measurements -- Periodicals; Scientific apparatus and instruments -- Periodicals; Equipment and Supplies -- Periodicals; Science -- instrumentation -- Periodicals; Technology -- instrumentation -- Periodicals; Mesures physiques -- Périodiques; Physical measurements; Scientific apparatus and instruments; Periodicals; 502.87
• DOI: 10.1088/1361-6501/abe083
• Languages: English
• ISSNs: 0957-0233

Abstract

Abstract: To provide a system with high-density solder joint 3D information acquisition and improve the comprehensive performance of automatic optical inspection systems, a novel diagnosis system for solder joints of high-density flexible integrated circuit substrates is proposed in this paper. The differential geometry principle is introduced to analyze the appearance identity of solder joints, and the diagnosis is handled as a pattern-recognition problem with the Frenet frame-matching approach. First, a high-precision 3D information-acquisition system constituted of two CCD digital cameras, each with a microscope and a three-color LED illumination, is developed. Second, a discrete estimation scheme based on the differential geometry theory is proposed to achieve curvature measurement, and then the shape of the solder joints is characterized by the crest line representation method. Finally, the classification strategy is to establish different models of solder joint types and make a decision based on a set of the predefined diagnosis rules. By inspecting various types of solder joints and comparing with other typical algorithms, the performance of the proposed system is evaluated. The experiment results indicate that the proposed algorithm has advantages of fast inspection speed, low misjudgment rate, which is reduced to 2.2%, and detailed classification.