New magnetic measurement system for determining metal covered mines by detecting magnetic anomaly using a sensor network

2015-03-01
EGE, Yavuz
KAKİLLİ, ADNAN
Citak, Hakan
Kalender, Osman
NAZLIBİLEK, SEDAT
Sensoy, Mehmet Gokhan
The most commonly used remote sensing methods are used in such applications as the aquistic emmission, ground penetration radar (GPR) detection, electromagnetic induction spectroscopy, infrared imaging, thermal neutron activation, nuclear quadruple resonance, X-ray back scattering, neutron back scattering and magnetic anomaly detection. In deciding which type of method has to be used for detection, the variables such as the type of object, material used, position, geographical and environmental conditions, etc. play important roles. In recent years, studies are mainly concentrated on the improvement of detection distance, accuracy, power consumption aspects of remote sensing methods. In the present study, the same concerns are taken into account and a new magnetic measurement system is developed in this context. The system is made up of a sensor network consisting of high sensitive and low power anisotropic magneto-resistive KMZ51 sensors. The sensor network can detect the magnetic anomalies of vertical component of earth's magnetic field created by buried objects as metal covered mines. In the present paper, the effects of physical properties of metal covered materials to magnetic anomalies have been studied. The sensor network is composed of 24 sensors. The voltage levels of each sensor are measured one-by one and transferred to a digital computer where the distribution of the voltages in x-y plane is plotted as 3D graphics. Furthermore, the performance of the system on the detection of buried metallic mines and determination of their shapes have been investigated.
INDIAN JOURNAL OF PURE & APPLIED PHYSICS

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Citation Formats
Y. EGE, A. KAKİLLİ, H. Citak, O. Kalender, S. NAZLIBİLEK, and M. G. Sensoy, “New magnetic measurement system for determining metal covered mines by detecting magnetic anomaly using a sensor network,” INDIAN JOURNAL OF PURE & APPLIED PHYSICS, pp. 199–211, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/68224.