journal article·2020-01-01Open access

Magnetic gradient full-tensor fingerprints for metallic objects detection of a security system based on anisotropic magnetoresistance sensor arrays

Huan Liu, Xiaobin Wang, Junchi Bin, Haobin Dong, Jian Ge, Zheng Liu, Zhiwen Yuan, Jun Zhu, Xinqun Luan

AIP Advances· Volume 10· Issue 1

Abstract

Concealed metallic object detection is one of the critical tasks for any security system. It has been proved that different objects have their own magnetic fingerprints, which are a series of magnetic anomalies determined by shape, size, physical composition, etc. This study addresses the design of a low-cost power security system for the detection of metallic objects according to their response to the magnetic field. The system consists of three anisotropic magnetoresistance (AMR) sensor arrays, detection circuits, and a microcontroller. A magnetic gradient full-tensor configuration, utilizing four AMR sensors arranged on a planar cross structure, was employed to construct a two-dimensional image from the obtained data, which can further suppress the background noise and reduce the orientation and orthogonality errors. The performance of the system is validated by data validation and multiple object feature segmentation. Numerous magnetic fingerprinting results demonstrate that the system can configure metallic objects more than 50cm clearly and identify multiple objects separated by less than 20 cm, which indicates the feasibility of using this magnetic gradient tensor fingerprint method for metallic object detection.
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Research context

OpenAlex topics: Non-Destructive Testing Techniques · Geophysical and Geoelectrical Methods · Geophysical Methods and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Automation, China University of Geosciences 1 , Wuhan, Hubei 430074, China

Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems 2 , Wuhan, Hubei 430074, China

Science and Technology on Near-Surface Detection Laboratory 3 , Wuxi, Jiangsu 214035, China

School of Engineering, University of British Columbia Okanagan Campus 4 , Kelowna, British Columbia V1V 1V7, Canada

Funding

Foundation of Science and Technology on Near-Surface Detection Laboratory · Foundation for Innovative Research Groups of the National Natural Science Foundation of China · National Key Research and Development Program of China Stem Cell and Translational Research

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