Abstract
Magnetic and inductive sensors are widely used in research and industry for a variety of applications, e.g. for geophysical prospecting, non-destructive testing (NDT) of materials, in the food industries, for distance and proximity sensing, security systems as well as for landmine detection. Metal detectors (MD), based on the eddy current principle, are the most used systems in humanitarian demining. Their main disadvantage is the high false alarm rate, caused by harmless metal objects and “uncooperative” soils with magnetic properties. The sensor signal (i.e. the induced complex coil voltage) is influenced by the object properties (material, shape). This paper describes an object recognition based on multi-parameter MD signals, which are classified by the fuzzy method. The ability to identify mines by their characteristic signature was demonstrated in test lanes for mine detection provided by the University of Rostock (Germany), JRC-Ispra (Italy) and the CTRO-Benkovac (Croatia).
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Krüger, H., Ewald, H. (2011). Signal Processing and Pattern Recognition for Eddy Current Sensors, Used for Effective Land-Mine Detection. In: Kamel, M., Karray, F., Gueaieb, W., Khamis, A. (eds) Autonomous and Intelligent Systems. AIS 2011. Lecture Notes in Computer Science(), vol 6752. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21538-4_29
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DOI: https://doi.org/10.1007/978-3-642-21538-4_29
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