Browsing by Subject "High sensitivity"

Now showing 1 - 5 of 5

Open Access
Identification of materials with magnetic characteristics by neural networks
(2012) Nazlibilek, S.; Ege, Y.; Kalender O.; Sensoy, M.G.; Karacor, D.; Sazli, M.H.
In industry, there is a need for remote sensing and autonomous method for the identification of the ferromagnetic materials used. The system is desired to have the characteristics of improved accuracy and low power consumption. It must also autonomous and fast enough for the decision. In this work, the details of inaccurate and low power remote sensing mechanism and autonomous identification system are given. The remote sensing mechanism utilizes KMZ51 anisotropic magneto-resistive sensor with high sensitivity and low power consumption. The images and most appropriate mathematical curves and formulas for the magnetic anomalies created by the magnetic materials are obtained by 2-D motion of the sensor over the material. The contribution of the paper is the use of the images obtained by the measurement of the perpendicular component of the Earth magnetic field that is a new method for the purpose of identification of an unknown magnetic material. The identification system is based on two kinds of neural network structures. The MultiLayer Perceptron (MLP) and the Radial Basis Function (RBF) network types are used for training of the neural networks. In this work, 23 different materials such as SAE/AISI 1030, 1035, 1040, 1060, 4140 and 8260 are identified. Besides the ferromagnetic materials, three objects are also successfully identified. Two of them are anti-personal and anti-tank mines and one is an empty can box. It is shown that the identification system can also be used as a buried mine identification system. The neural networks are trained with images which are originally obtained by the remote sensing system and the system is operated by images with added Gaussian white noises. © 2012 Elsevier Ltd. All rights reserved.
Open Access
Metamaterial based telemetric strain sensing in different materials
(Optical Society of American (OSA), 2010) Melik, R.; Unal, E.; Perkgoz, N.K.; Puttlitz, C.; Demir, Hilmi Volkan
We present telemetric sensing of surface strains on different industrial materials using split-ring-resonator based metamaterials. For wireless strain sensing, we utilize metamaterial array architectures for high sensitivity and low nonlinearity-errors in strain sensing. In this work, telemetric strain measurements in three test materials of cast polyamide, derlin and polyamide are performed by observing operating frequency shift under mechanical deformation and these data are compared with commercially-available wired strain gauges. We demonstrate that hard material (cast polyamide) showed low slope in frequency shift vs. applied load (corresponding to high Young's modulus), while soft material (polyamide) exhibited high slope (low Young's modulus).
Open Access
Metamaterial-based wireless strain sensors
(American Institute of Physics, 2009-07-07) Melik, R.; Unal, E.; Perkgoz, N. K.; Puttlitz, C.; Demir, Hilmi Volkan
We proposed and demonstrated metamaterial-based strain sensors that are highly sensitive to mechanical deformation. Their resonance frequency shift is correlated with the surface strain of our test material and the strain data are reported telemetrically. These metamaterial sensors are better than traditional radio-frequency (rf) structures in sensing for providing resonances with high quality factors and large transmission dips. Using split ring resonators (SRRs), we achieve lower resonance frequencies per unit area compared to other rf structures, allowing for bioimplant sensing in soft tissue (e.g., fracture healing). In 5×5 SRR architecture, our wireless sensors yield high sensitivity (109 kHz/kgf, or 5.148 kHz/microstrain) with low nonlinearity error (<200 microstrain).
Open Access
Numerical analysis for remote identification of materials with magnetic characteristics
(2011) Ege, Y.; Şensoy, M.G.; Kalender O.; Nazlibilek, S.
There is a variety of methods used for remote sensing of objects such as acoustic, ground penetration radar detection, electromagnetic induction spectroscopy, infrared imaging, thermal neutron activation, core four-pole resonance, neutron backscattering, X-ray backscattering, and magnetic anomaly. The method that has to be used can be determined by the type of material, geographical location (underground or water), etc. Recent studies have been concentrated on the improvement of the criteria such as sensing distances, accuracy, and power consumption. In this paper, anomalies created by materials with magnetic characteristics at the perpendicular component of the Earth magnetic field have been detected by using a KMZ51 anisotropic magnetoresistive sensor with high sensitivity and low power consumption, and also, the effects of physical properties of materials on magnetic anomaly have been investigated. By analyzing the graphics obtained by 2-D motion of the sensor over the material, the most appropriate mathematical curves and formulas have been determined. Based on the physical properties of the magnetic material, the variations of the variables constituting the formulas of the curves have been analyzed. The contribution of this paper is the use of the results of these analyses for the purpose of identification of an unknown magnetic material. This is a new approach for the detection and determination of materials with magnetic characteristics by sensing the variation at the perpendicular component of the Earth magnetic field. The identification process has been explained in detail in this paper. © 2011 IEEE.
Open Access
Weighing graphene with QCM to monitor interfacial mass changes
(American Institute of Physics Inc., 2016) Kakenov, N.; Balci, O.; Salihoglu, O.; Hur, S. H.; Balci, S.; Kocabas, C.
In this Letter, we experimentally determined the mass density of graphene using quartz crystal microbalance (QCM) as a mechanical resonator. We developed a transfer printing technique to integrate large area single-layer graphene on QCM. By monitoring the resonant frequency of an oscillating quartz crystal loaded with graphene, we were able to measure the mass density of graphene as ∼118 ng/cm2, which is significantly larger than the ideal graphene (∼76 ng/cm2) mainly due to the presence of wrinkles and organic/inorganic residues on graphene sheets. High sensitivity of the quartz crystal resonator allowed us to determine the number of graphene layers in a particular sample. Additionally, we extended our technique to probe interfacial mass variation during adsorption of biomolecules on graphene surface and plasma-assisted oxidation of graphene.