Browsing by Author "Atan, O."

Now showing 1 - 5 of 5

Distributed Bearing Fault Classification of Induction Motors Using 2-D Deep Learning Model
(Institute of Electrical and Electronics Engineers Inc., 2024) Rajabioun, R.; Afshar, M.; Mete, M.; Atan, O.; Akin, B.
Distributed bearing faults are highly common in industrial applications and display unpredictable vibration patterns impeding their detection. These faults stem from issues such as lubrication deficiencies, contamination, electrical erosion, roughness of the bearing surface, or the propagation of localized faults. This study aims to detect distributed bearing faults by utilizing a multisensory approach consisting of current, accelerometer, and fluxgate sensors. A novel 2-D deep learning framework is proposed, leveraging signals from six distinct sources, including three-axis vibration signals, stray magnetic flux signal, and two-phase current signals. Data are collected from 3- and 10-hp induction motors at 50 operational points, spanning ten speed levels and five torque levels. These six signals are transformed into matrices and combined to create a comprehensive matrix that provides an overall depiction of the bearing condition. The proposed deep learning architecture employs a 2-D convolutional model, which takes 2-D images as input and determines the bearing status. To evaluate the system's robustness, the data are divided into training and testing sets. The proposed model demonstrates remarkable effectiveness in detecting distributed bearing faults, achieving an impressive accuracy rate of 99.92%. Furthermore, a comprehensive comparison is provided, highlighting the impact of using various sets of inputs as sources for the deep learning model on the accuracy rate for each set. Through the analysis of the obtained results, a clear conclusion can be drawn: the model performs at its best when all six input sources are utilized. © 2025 Elsevier B.V., All rights reserved.
Evaluation of Carcinogenic Effects of Electromagnetic Fields (Emf)
(2010) Bayazit, V.; Bayram, B.; Pala, Z.; Atan, O.
The purpose of this study was to investigate the carcinogenic effects of electromagnetic fields on human. There are many effects of electromagnetic fields on human such as cancer, epidemiology, acute and chronic effects. These effects vary according to the field strength and environmental conditions. There have been many instances of harmful effects of electromagnetic fields from such seemingly innocuous devices as mobile phones, computers, power lines and domestic wiring. The balance of epidemiologic evidence indicates that mobile phone use of less than 10 years does not pose any increased risk of brain tumour or acoustic neuroma. For long-term use, data are sparse, and the following conclusions are therefore uncertain and tentative.
Fuzzy Variable Order Extremum-Seeking Controller Design for Mobile Robots
(2019) Atan, O.
In this paper, a fuzzy variable order extremum-seeking control (FVO-ESC) system for a mobile robot are designed. Fractional order controllers have advantages in the control of nonlinear systems such as a wider area of stability and performance enhancement in the presence of noise. The main proposal of the paper is to increase the performance of the fractional order controller. So, a variable order controller was designed for a mobile robot, and a fuzzy logic controller was designed according to user experiences to tune the controller order. The proposed FVO-ESC approach has been validated the effects on nonlinear systems such as the mobile robot system. It has been put forward in the preliminary investigation that the order of the fractional order ESC controller affects the overshoot and time to reach the target. The results suggested that a variable-level controller would have better performance. The results show that the proposed FVO-ESC control approach provides optimum performance for mobile robot systems.
An Image Encryption Algorithm Using Ikeda and Henon Chaotic Maps
(Institute of Electrical and Electronics Engineers Inc., 2017) Sekertekin, Y.; Atan, O.
In this paper, an image encryption algorithm based on Ikeda and Henon chaotic maps is presented. One of the most used in image encryption techniques which is shuffling and diffusion combination is used in this study. Firstly rows and columns of the image are shuffled by Ikeda map and then gray levels of pixels are changed by Henon map. After that, Ikeda Map is used again to shuffle the image which is changed the pixels. Some tests including key sensitivity analysis, statistical tests and several experimental tests are used to evaluate the developed algorithm. The results show that the algorithm is a secure way to encrypt the images efficiently. © 2016 IEEE.
Transmission and Decryption of the Audio Signal Masked With Ecg by Fdm Method
(Springer int Publ Ag, 2022) Parlar, I; Almali, M. N.; Atan, O.; Cabuker, A. C.; Silahtar, O.
Today, the use of these methods as hybrids has provided the motivation to be a solution to important problems, since the existing methods are insufficient at some points in ensuring the security of personal data. In data security, the inability to decrypt and decrypt the signal to be encrypted retrospectively has always been the subject of research in terms of privacy. At this point, it was preferred to use the electrocardiography (ECG) signal, which is a signal that shows the vital signs of the human body and is also difficult to copy. In the study, firstly, the emulator circuit was obtained by using the mathematical model of the ECG signal. With this obtained signal, the audio signals are masked. The audio signal masked on the transmitter side and the signals providing synchronization were transmitted to the receiver side over a single channel using the frequency division multiplexing (FDM) method. Then, the sliding mode control (SMC) method was chosen for the synchronization of the ECG emulator circuits on the receiver and transmitter side. Histogram, spectral, mean square error (MSE), peak signal to noise ratio (PSNR), key space and key sensitivity, NSCR (number of sample change rate), UACI (unified average changing intensity) and PESQ (perceptual evaluation of speech quality) analyses were used to check the accuracy of the system. These analyses showed that the ECG encoding method has faster unit change, reduces synchronization time, minimizes losses and improves the security of the masked signal compared to other methods sent from two channels. Finally, use of an arrhythmia ECG signal for the synchronization signal on both the transmitter and receiver sides, the synchronization of this signal with the SMC method and the testing of a live audio recording in addition to the conversation, distinguishes the study from other existing studies and reveals its originality.