Nazlıbilek, Sedat

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https://hdl.handle.net/20.500.14411/8361
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S.,Nazlibilek
N., Sedat
Nazlıbilek,S.
Sedat, Nazlıbilek
N.,Sedat
Nazlibilek,S.
S., Nazlibilek
S.,Nazlıbilek
Sedat, Nazlibilek
Nazlıbilek, Sedat
Nazlibilek, Sedat
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Doçent Doktor
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Department of Mechatronics Engineering
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Former Staff
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7

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10

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15

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Scholarly Output

22

Articles

14

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Supervised MSc Theses

3

Supervised PhD Theses

3

WoS Citation Count

243

Scopus Citation Count

302

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7

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8

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WoS Citations per Publication

11.05

Scopus Citations per Publication

13.73

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1

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6

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JournalCount
Measurement7
Indian Journal of Pure and Applied Physics2
IEEE Transactions on Instrumentation and Measurement2
20th Annual International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2013 -- 20th Annual International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2013 -- 20 September 2013 through 20 September 2013 -- Ankara -- 1022761
International Conference of Control, Dynamic Systems, and Robotics -- 4th International Conference of Control, Dynamic Systems, and Robotics, CDSR 2017 -- 21 August 2017 through 23 August 2017 -- Toronto -- 1399181
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Has files: falseSubject: Magnetic anomaly

Scholarly Output Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    Article
    Citation - WoS: 10
    Citation - Scopus: 12
    Anomaly Detection With Low Magnetic Flux: a Fluxgate Sensor Network Application
    (Elsevier Sci Ltd, 2016) Ege, Yavuz; Coramik, Mustafa; Kabadayi, Murat; Citak, Hakan; Kalender, Osman; Yuruklu, Emrah; Nazlibilek, Sedat
    Recent studies on remote detection methods were mostly for improving variables like sensing distance, sensitivity and power consumption. Especially using anisotropic magneto-resistive sensors with low power consumption and high sensitivity for detecting subsurface magnetic materials became very popular in last decades. In our study, for detecting subsurface materials, we have used fluxgate sensor network for having even higher sensitivity and also minimizing the power consumption by detecting the changing rates of horizontal component of earth's magnetic flux which is assumed to be very low. We have constituted a magnetic measurement system which comprises a detector system, which has a mechanism enables sensors to move in 3-D space, a data acquisition module for processing and sending all sensor information, and a computer for running the magnetic flux data evaluation and recording software. Using this system, tests are carried out to detect anomalies on horizontal component of earth's magnetic flux which is created by different subsurface materials with known magnetic, chemical and geometric properties. The harmonics of horizontal component of earth's magnetic flux in scanned area are analyzed by the help of DSP Lock-In amplifier and the amplitudes of high variation harmonics are shown as computer graphics. Using the graphic information, the upside surface geometry of subsurface material is defined. For identifying the magnetic anomalies, we have used the scale-invariant feature transform (SIFT)-binary robust invariant scalable keypoints (BRISKs) as keypoint and descriptor. We used an algorithm for matching the newly scanned image to the closest image in database which is constituted of mines and possible other metal objects like cans, etc. Results show that, if the proposed detection system is used instead of metal detectors which cannot distinguish mines from other metal materials and alert for every type of metal with different geometries, it can be said that miss alarm count, work force and time can be decreased dramatically. In this paper, mostly the setup of the system is described and in Appendix A some experimental outputs of the system for different geometries of metal samples are given. And also for comparing the results of the proposed system, additional experiments are carried out with a different type of sensor chip, namely KMZ51, and also given in Appendix A. (C) 2015 Elsevier Ltd. All rights reserved.
  • Thumbnail Image
    Article
    Citation - WoS: 19
    Citation - Scopus: 19
    Identification of Materials With Magnetic Characteristics by Neural Networks
    (Elsevier Sci Ltd, 2012) Nazlibilek, Sedat; Ege, Yavuz; Kalender, Osman; Sensoy, Mehmet Gokhan; Karacor, Deniz; Sazh, Murat Husnu
    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. Crown Copyright (C) 2012 Published by Elsevier Ltd. All rights reserved.
  • Thumbnail Image
    Article
    Citation - WoS: 7
    Citation - Scopus: 10
    Autonomous Navigation of Robotic Units in Mobile Sensor Network
    (Elsevier Sci Ltd, 2012) Nazlibilek, Sedat
    This work is motivated by the problem of detecting buried anti-tank and anti-personnel mines in roads or some border regions. The problem is tried to be solved by use of small mobile robotic sensors and their some abilities such as measurement of local fields, navigation around a region, communications with each other, and constituting team within a mission area. The aim of this work is to investigate the navigation problem for the team behavior of mobile sensors within a potential field available in a small-scale environment such as an indoor area or an outdoor region. The mobile sensor network here is a collection of robotic units with sensing capability of earth magnetic field anomalies. A new kind of positioning system is needed for their collective behavior. In this work, a new method of navigation is proposed as a local positioning system. It utilizes ultrasound and radio frequency information to determine the coordinates of the points inside the operational area. The method proposed here is compared with the ultra wideband ranging ping-pong method that is used widely in recent applications. A time division multiple access method is used for the communications among the mobile sensors. The results on the positioning methods together with several simulations and experimental works are given. It is shown that the positioning method utilizing ultrasound-radio frequency method can give fairly good results. (C) 2012 Elsevier Ltd. All rights reserved.