Magnetic Polarizability Tensor Spectroscopy for Low Metal Anti-Personnel Mine Surrogates

Abdel-Rehim, Omar A.; Davidson, Jennifer L.; Marsh, Liam A; O’Toole, Michael D.; Peyton, A. J.

doi:10.1109/jsen.2016.2535346

Cited by 42 publications

(50 citation statements)

References 16 publications

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“…Proof. Using Lemma 3.1, we immediately establish that C(u, v) vanishes for = 0 and, from (11), find that (1)…”

Section: Limiting Cases Of mentioning

confidence: 83%

“…To provide an alternative splitting of , we generalise Lemma 1 of Ledger and Lionheart, 13 which was for a homogenous object, to the inhomogeneous case, in terms of (u) = (0) (u) + (1)…”

Section: Invariant Form Of mentioning

confidence: 99%

“…Note that  * −  * = (N * (e i , e ) − C * (e i , e ))e i ⊗ e is a complex rank 2 tensor, and  0 = N 0 (e i , e )e i ⊗ e is a real rank 2 tensor. The forms C * , N * , and N 0 depend on the solutions (0) (u), (1) (u) to the transmission problems…”

Section: Invariant Form Of mentioning

confidence: 99%

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The spectral properties of the magnetic polarizability tensor for metallic object characterisation

Ledger

Lionheart

2019

Math Methods in App Sciences

113

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The measurement of time-harmonic perturbed field data, at a range of frequencies, is beneficial for practical metal detection, where the goal is to locate and identify hidden targets. In particular, these benefits are realised when frequency-dependent magnetic polarizability tensors (MPTs) are used to provide an economical characterisation of conducting permeable objects, and a dictionary-based classifier is employed. However, despite the advantages shown in dictionary-based classifiers, the behaviour of the MPT coefficients with frequency is not properly understood. In this paper, we rigorously analyse, for the first time, the spectral properties of the coefficients of the MPT. This analysis has the potential to improve existing algorithms and design new approaches for object location and identification in metal detection. Our analysis also enables the response transient response from a conducting permeable object to be predicted for more general forms of excitation. KEYWORDSasymptotic analysis, eddy current, inverse problems, magnetic polarizability tensor, metal detection, spectral problems MSC CLASSIFICATION 35R30; 35B30 INTRODUCTIONIn metal detection, there is considerable interest in being able to locate and identify conducting permeable objects from the measurements of mutual inductance between a transmitting and a measurement coil. Applications include security screening, archaeology excavations, ensuring food safety as well as the search for land mines, and unexploded ordnance. There are also closely related topics such as magnetic induction tomography for medical imaging and eddy current testing for monitoring the corrosion of steel reinforcement in concrete structures.Within the metal detection community, magnetic polarizability tensors (MPTs) have attracted considerable interest to assist with the identification of objects when the transmitting coil is excited by a sinusoidal signal, eg, 1-7 Engineers believe that a rank 2 MPT provides an economical characterisation of a conducting permeable object that is invariant of position. An asymptotic formula providing the leading order term for the perturbed magnetic field due to the presence of a small conducting permeable object has been obtained by Ammari, Chen, Chen, Garnier, and Volkov, 8 which characterises the object in terms of a rank 4 tensor. We have shown that this simplifies for orthonormal coordinates and allows an object to be characterised by a complex symmetric rank 2 MPT, with an explicit formula for its coefficients, thus, justifying the This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Proof. Using Lemma 3.1, we immediately establish that C(u, v) vanishes for = 0 and, from (11), find that (1)…”

Section: Limiting Cases Of mentioning

confidence: 83%

“…To provide an alternative splitting of , we generalise Lemma 1 of Ledger and Lionheart, 13 which was for a homogenous object, to the inhomogeneous case, in terms of (u) = (0) (u) + (1)…”

Section: Invariant Form Of mentioning

confidence: 99%

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The spectral properties of the magnetic polarizability tensor for metallic object characterisation

Ledger

Lionheart

2019

Math Methods in App Sciences

113

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“…By plotting the complex components of the secondary field with respect to the excitation (H S /H tx ) at different frequencies, we can generate the impedance spectra shown in figure 1. The shape of the real and imaginary curves in this figure are characteristic for nonmagnetic conductive objects [3], [6] . We make two observations: (1) The imaginary component at frequencies along the loss-curve is a function of the conductivity and geometry of the object, and (2) the real component at high frequencies -close to the asymptote -is insensitive to conductivity and is mostly a function of the object geometry.…”

Section: Theorymentioning

confidence: 99%

“…Classification based on spectral response has been investigated for identifying clutter in landmine detection [2], [3]. Further, we have previously used single-frequency magnetic polarisability tensor measurements [4] and fast boundary element solver for this application [5].…”

Section: Introductionmentioning

confidence: 99%

Fast classification of non-magnetic metal targets using eddy-current based impedance spectroscopy

2017

Self Cite

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Abstract-We present a new method to sort non-magnetic conductive metals -specifically brass, copper and aluminiumwith the aim of improving economic yields in the scrap metal and recycling industries. The method uses the impedance spectra of the metal objects derived from the scattered magnetic field. Preliminary results are presented on a small sample set showing good accuracy across all metal classes even when the test objects are travelling at high speeds (1 m/s). The results suggest the method is both feasible and practical at the high-throughput demanded by industry.

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Efficient computation of the magnetic polarizabiltiy tensor spectral signature using proper orthogonal decomposition

Wilson

Ledger

2021

Numerical Meth Engineering

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The identification of hidden conducting permeable objects from measurements of the perturbed magnetic field taken over a range of low frequencies is important in metal detection. Applications include identifying threat items in security screening at transport hubs, location of unexploded ordnance, and antipersonnel landmines in areas of former conflict, searching for items of archeological significance and recycling of valuable metals. The solution of the inverse problem, or more generally locating and classifying objects, has attracted considerable attention recently using polarizability tensors. The magnetic polarizability tensor (MPT) provides a characterization of a conducting permeable object using a small number of coefficients, has an explicit formula for the calculation of their coefficients, and a well understood frequency behavior, which we call its spectral signature. However, to compute such signatures, and build a library of them for object classification, requires the repeated solution of a transmission problem, which is typically accomplished approximately using a finite element discretization. To reduce the computational cost, we propose an efficient reduced order model (ROM) that further reduces the problem using a proper orthogonal decomposition for the rapid computation of MPT spectral signatures. Our ROM benefits from a posteriori error estimates of the accuracy of the predicted MPT coefficients with respect to those obtained with finite element solutions. These estimates can be computed cheaply during the online stage of the ROM allowing the ROM prediction to be certified. To further increase the efficiency of the computation of the MPT spectral signature, we provide scaling results, which enable an immediate calculation of the signature under changes in the object size or conductivity. We illustrate our approach by application to a range of homogenous and inhomogeneous conducting permeable objects.

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Magnetic Polarizability Tensor Spectroscopy for Low Metal Anti-Personnel Mine Surrogates

Cited by 42 publications

References 16 publications

The spectral properties of the magnetic polarizability tensor for metallic object characterisation

The spectral properties of the magnetic polarizability tensor for metallic object characterisation

Fast classification of non-magnetic metal targets using eddy-current based impedance spectroscopy

Efficient computation of the magnetic polarizabiltiy tensor spectral signature using proper orthogonal decomposition

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