Using RBF algorithm for Scanning Acoustic Microscopy inspection of flip chip
With the increasing prevalence of flip-chip technology in high density assembly,more attention has been paid to the microbump defect inspection in the flip chip.However,the traditional techniques have some disadvantages,which makes it difficult to diagnose the chips efficiently.Therefore,new inspection approaches for solder bump are being investigated.In this article,the radial basis function neural network(RBF)combined with the scanning acoustic microscopy(SAM)technology is proposed for inspection of missing microbump defects.The ultrasonic transducer was used to test the flip chip.The solder joints were segmented from the SAM image on the basis of gradient of gray scale,and representative characteristics of micro solder balls were extracted.Then RBF network was used for identification.The results reflect that RBF algorithm with high recognition rate is effective for diagnosis of missing-bump defects.
Microbump SAM technology RBF algorithm
Fan Liu Mengying Fan Zhenzhi He Xiangning Lu
School of Mechanical & Electrical Engineering Jiangsu Normal University Xuzhou,China
国际会议
上海
英文
112-114
2018-08-08（万方平台首次上网日期，不代表论文的发表时间）