Fast and accurate yield rate prediction of PCB embedded common-mode filter with artificial neural network
Journal
IEEE International Symposium on Electromagnetic Compatibility and 2018 IEEE Asia-Pacific Symposium on Electromagnetic Compatibility (EMC/APEMC)
Date Issued
2018
Author(s)
Abstract
A fast and accurate yield rate prediction method of PCB embedded Common-Mode Filter (CMF) is proposed and implemented by applying artificial neural network (ANN), one of machine learning techniques. The proposed CMF is a mushroom-like structure which has four metal layers. The frequency responses of full-wave simulation and the outputs of trained ANN have good consistency. Furthermore, a substantial number of data sets with specific deviations can be applied with trained ANN to predict yield rate and find out sensitive parameters quickly.
Type
conference paper