Radiated EMI Recognition and Identiffication from PCB Configuration Using Neural Network
In this paper the application of neural network (NN) in EMI radiated measurement is proposed to recognize and identify the basic PCB configuration. The emission of effectromagnetic (EMI) noise form printed circuit board (PCB) is studied. The different kinds of PCB shape are used for produce effectromagnetic field. The fields are measured using near-field probe with termination load and computation using finite element method (FEM). After measurement by near-field probe and simulation by FEM then, is a thinning process. The images acquired from thinning process will be analyzed to calculate number of junction point, end point, cross point, ratio of black and white, position of end point, vertical line and horizontal line, respectively then pass to NN. The trained NN can identify emission pattern successfully.
P. Sujintanarat P. Dangkham S. Chaichana K. Aunchaleevarapan P. Teekaput
Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand Electrical and Electronic Products Testing Center, NECTEC, NSTDA, KMITL Bangkok, Thailand
国际会议
Progress in Electromagnetics Research Symposium 2007(2007年电磁学研究新进展学术研讨会)(PIERS 2007)
北京
英文
1028-1032
2007-03-26（万方平台首次上网日期，不代表论文的发表时间）