The Analytical and Artificial Intelligence Methods to Investigate the Effects of Aperture Dimension Ratio on Electrical Shielding Effectiveness

This paper presents that the effect of single aperture size of metallic enclosure on electrical shielding effectiveness (ESE) at 0 – 1 GHz frequency range has been investigated by using both Robinson’s analytical formulation and artificial neural networks (ANN) methods that are multilayer perceptron (MLP) networks and a radial basis function neural network (RBFNN). All results including measurement have been compared each other in terms of aperture geometry of metallic enclosure. The geometry of single aperture varies from square to rectangular shape while the open area of aperture is fixed. It has been observed that network structure of MLP 3-40-1 in modeling with ANN modeled with fewer neurons in the sense of overlapping of faults and data and modeled accordingly. In contrast, the RBFNN 3-150-1 is the other detection that the network structure is modeled with more neurons and more. It can be seen from the same network-structured MLP and RBFNN that the MLP modeled better. In this paper, the impact of dimension of rectangular aperture on shielding performance by using RBFNN and MLP network model with ANN has been studied, as a novelty.

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This work was supported by The Department of Scientific Research Projects in Suleyman Demirel University named as "Investigation the Effect on Total Electromagnetic Emission Distribution of Metallic Enclosure Topology" and in Turkish "Metalik Kutulama Topolojisinin Toplam Elektromanyetik Emisyon Dağılımına Etkisinin İncelenmesi" [4384-D2-15].