Determination of Electromagnetic properties of Concrete Using Microwave Non-Destructive testing techniques and Artificial neural networks

Abstract

Every year, a massive amount of literature is published on many aspects of microwave applications. Over the past few years, the need for progressive methods for assessing different properties of concrete, as well as for maintenance and monitoring of structures, has led to the development of microwave nondestructive testing (MNDT) techniques for preserving the civil infrastructure. As the number of studies being published in this eld is growing fast, it is important to categorize the studies at deeper levels. In this paper, a concrete cube of M20 grade has been created in ANSYS HFSS for simulation purposes. An arti cial rectangular crack was developed in the concrete cube and the simulation was run at dielectric constants from 1-10 with 0.5 intervals, loss tangents from 0.001,0.1 &0.2, and the gap between sample and circular waveguide from 0-7cm with 1cm interval. The arti cial neural network was developed in python for Mean square Error(MSE) analysis and prediction of Electromagnetic properties(Dielectric constant and Loss tangent) with inputs as the S-parameter(real and imaginary) data of the Homogenous sample and sample with Rectangular crack. The result analysis shows the variation in Mean squared error for crack and No-crack concrete samples.