Yazar "Demetgul, Mustafa" seçeneğine göre listele

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    Fingerprinting the Lamb Wave Signals by Using S-Transformation
    (Spie-Int Soc Optical Engineering, 2012) Tansel, Ibrahim N.; Yapici, Ahmet; Korla, Srikanth; Demetgul, Mustafa
    Lamb wave method detects the defects from the propagation characteristics of the created brief harmonic signals. Generally, the defects are detected by analyzing the delays and amplitudes of the received waves. The envelopes of the sensory signals may be used to calculate the delays and amplitudes of the received signals. Sometimes, similar envelopes could be observed at different test conditions. Use of the time-frequency spectra of the s-transformation is proposed for distinction of the problems when the envelopes of the monitored signals are very similar. In the study, a beam was compressed from different points with a hydraulic crimping tool. In separate tests, the cross sectional area at the middle of the beam was reduced by opening slots. The envelopes and time-frequency spectra of the sensory signals were calculated by using the s-transformation. The difference of the time-frequency spectra successfully distinguished the test condition when the envelopes were very similar.
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    Optimizations of friction stir welding of aluminum alloy by using genetically optimized neural network
    (Springer London Ltd, 2010) Tansel, Ibrahim N.; Demetgul, Mustafa; Okuyucu, Hasan; Yapici, Ahmet
    Genetically optimized neural network systems (GONNS) was developed to simulate the intelligent decision-making capability of human beings. After they are trained with experimental data or observations, GONNS use one or more artificial neural networks (ANN) to represent complex systems. The optimization is performed by one or more genetic algorithms (GA). In this study, the GONNS was used to estimate the optimal operating condition of the friction stir welding (FSW) process. Five separate ANNs represented the relationship between two identical input parameters and each one of the considered characteristics of the welding zone. GA searched for the optimized parameters to make one of the parameters maximum or minimum, while the other four are kept within the desired range. The GONNS was found as an excellent optimization tool for FSW.