Open AccessA Very-Low-Frequency Electromagnetic Inductive Sensor System for Workpiece Recognition Using the Magnetic Polarizability Tensor
Author(s) -
Yang Tao,
Wuliang Yin,
Wenbo Zhang,
Yifei Zhao,
Christos Ktistis,
Anthony J. Peyton
Publication year - 2017
Publication title -
ieee sensors journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.681
H-Index - 121
eISSN - 1558-1748
pISSN - 1530-437X
DOI - 10.1109/jsen.2017.2676460
Subject(s) - signal processing and analysis , communication, networking and broadcast technologies , components, circuits, devices and systems , robotics and control systems
The automatic recognition of a metal component or workpiece currently relies on optical techniques and image matching. It is not possible to distinguish workpieces with different materials. In this paper, a novel electromagnetic inductive sensor array similar to those used in the electromagnetic tomography has been designed to address this problem. Furthermore, instead of reconstructing the full magnetic polarizability tensor, we have proposed a partial tensor approach, which shows that a 2-D tensor is capable of distinguishing the material difference and recognising the geometric dominance of workpieces with experimental data. In addition, it has been found that the phase of the tensor is strongly linked to the materials properties while the magnitude of the tensor eigenvalues implies the basic geometry of workpiece.