Computer model for detecting the metal objects with induction metal detector.

The relevance of the article is to highlight the process of creating a computer model of metal object detection in theCOMSOL Multiphysics environment and the results of its application. Its use will increase the efficiency of the use of induction metal detectors, which is extremely important under war conditions, as it will allow better and faster detection of metal explosive objects.One of the most common in terms of price/quality ratio for detecting metal objects is the single-circuit resonant inductivemetal detector, which has certain structural features. The ability to detect metal objects is provided by a system of inductioncoils, the most common of which is the Double D type system. The problem of calculating the induction of the magnetic fieldgenerated by a coil in any region (set of points) of space is therefore very complex and difficult to solve mathematically.Moreover, its complexity is directly proportional to the number of these points.The purpose of the article is to develop a computer model for the detection of metal objects for an inductive metal detectorwith a double D-coil system, to configure its parameters using the example of a real Fischer F5 metal detector, to analyse theresults of the application with the determination of the possible directions of use of the created model, as well as the features and limitations of its application.The article presents the results of creating a three-dimensional model of the metal object detection system, describes itsmain parameters, and lists the interfaces and tools used in the COMSOL environment. Graphs and colour maps show thedependence of the voltage induced in the receiver coil and the phase difference between the currents of the two coils on the position of a cylindrical metal target as it moves in the horizontal and vertical planes, as its geometric dimensions change and as its specific electrical conductivity changes (corresponding to the change in metal). The limits of the geometric dimensions and the distance of the target from the system where detection becomes unlikely are determined.The conclusions emphasise the significance of the results obtained, as well as possible directions for the application ofthe developed model and the benefits of its use.