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Materials, Methods & Technologies, Volume 10, 2016

Fernandez-Perez Nora, Gamallo-Ponte Pablo
Pages: 25-44
Published: 30 Apr 2016
Views: 2,065
Downloads: 545
Abstract: This paper describes the study carried out to identify the involved parameters and its effects, in surface defect detection of metallic pieces through electromagnetic induction. The technique is known by Induction Thermography, and the detection under the produced electrical field occurs due to the induced current concentration on the edges of the defects that can be finally detected by a thermographic camera. To aid in the analysis of the problem, involved physics as well as the related parameters, a simulation method was developed. A coupled electromagnetic and thermal finite element model was created with the software ANSYS. Through this method the influence of the different variables involved, such as geometry or configuration (dimensions, shape, location, orientation, etc.) and the electrical or input parameters, as well as the time dependency was assessed in the obtained simulation results. In fact the evidence about the detection process effectiveness and efficiency was studied, based on data such as induced current density concentration, heating uniformity, electrical power required, cycle time, etc. Thus the goal of this paper is to find out the influence of the different configurations and variables involved, to finally provide a system with the best result in terms of reduced energy and time consumption. This model is the result of a previously validated work (ref), and thus it is a consistent and reliable tool for induction heating analyses and for the optimization of surface crack detection processes based on Induction thermography. It will highly reduce time and economic investments, prior to the physical construction and tests of the system.
Keywords: electromagnetic induction, induction thermography, electro-thermal modeling, numerical simulation
Cite this article: Fernandez-Perez Nora, Gamallo-Ponte Pablo. ELECTROMAGNETIC INDUCTION SIMULATION FOR DEFECTS DETECTION: INVOLVED VARIABLES AND ITS EFFECTS. Journal of International Scientific Publications: Materials, Methods & Technologies 10, 25-44 (2016).
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