Mekatronik Mühendisliği Bölümü Yayın Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/255

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Citation - WoS: 2
Citation - Scopus: 2
Control structure design with constraints for a slung load quadrotor system
(Sage Publications Ltd, 2024) Ergezer, Halit; Ergezer, Halit; Leblebicioglu, Kemal; 293396
We propose a control structure for a quadrotor carrying a slung load with swing-angle constraints. This quadrotor is supposed to pass through the waypoints at specified speeds. First, a cascaded PID autopilot is designed, which adaptively gives attention to position and speed requirements as a function of their errors. Its parameters are found from an optimization problem solved using the PSO algorithm. Second, this controller's performance is improved by adding the Complementary Controller employing an ANN. 5. Training data for the ANN is created by solving optimal control problems. The ANN is activated when the swing angle constraint is about to be violated. It is trained using optimal control values corresponding to the cases where the swing angle falls in a particular band about the upper swing angle constraint. Simulations are performed in a MATLAB environment. Finally, some of the simulation results are validated on a physical system.
Citation - WoS: 6
Citation - Scopus: 6
Design and implementation of an electrode feed rate control system in the electrochemical drilling process
(Springer Heidelberg, 2022) Ozerkan, Haci Bekir; Çoğun, Can; Cogun, Can; 3837
The interelectrode gap distance control is essential for preventing short circuit and spark discharge occurrences in the machining gap and ensuring a constant distance between the tool electrode (shortly electrode) and the workpiece throughout the electrochemical drilling (ECD) process. In this study, a gap distance control system was designed and implemented in the constructed ECD machine tool. The gap distance control strategy was based on the machining current's discrete measurement (in microsecond intervals) and changing the gap distance according to a set current value by feeding the electrode towards the workpiece or retracting it during the ECD process. The small diameter deep hole ECD experiments were conducted using 0.5 mm diameter side insulated tubular rotational electrodes with through-hole electrolyte flushing to drill Hadfield and AISI 1040 steels. The experimental results demonstrated the success of the developed control system in ECD operations yielding uniform hole geometries and smooth hole surfaces. The use of the control system eliminated the undesirable formations of spark discharges and short circuit pulses.
Citation - WoS: 8
Citation - Scopus: 10
Developing and Implementation of an Optimization Technique for Solar Chimney Power Plant With Machine Learning
(Asme, 2021) Ulucak, Oguzhan; Beldek, Ulaş; Kocak, Eyup; Bayer, Ozgur; Beldek, Ulas; Yapic, Ekin Ozgirgin; Ayli, Ece; 59950; 31329; 265836
Green energy has seen a huge surge of interest recently due to various environmental and financial reasons. To extract the most out of a renewable system and to go greener, new approaches are evolving. In this paper, the capability of Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System in geometrical optimization of a solar chimney power plant (SCPP) to enhance generated power is investigated to reduce the time cost and errors when optimization is performed with numerical or experimental methods. It is seen that both properly constructed artificial neural networks (ANN) and adaptive-network-based fuzzy inference system (ANFIS) optimized geometries give higher performance than the numerical results. Also, to validate the accuracy of the ANN and ANFIS predictions, the obtained results are compared with the numerical results. Both soft computing methods over predict the power output values with MRE values of 12.36% and 7.25% for ANN and ANFIS, respectively. It is seen that by utilizing ANN and ANFIS algorithms, more power can be extracted from the SCPP system compared to conventional computational fluid dynamics (CFD) optimized geometry with trying a lot more geometries in a notably less time when it is compared with the numerical technique. It is worth mentioning that the optimization method that is developed can be implemented to all engineering problems that need geometric optimization to maximize or minimize the objective function.
Citation - WoS: 5
Citation - Scopus: 5
Dynamic flat-topped laser beam shaping method using mixed region amplitude freedom algorithm
(Springer Heidelberg, 2022) Alsaka, Dina Yaqoob; Arpali, Çağlar; Arpali, Caglar; Arpali, Serap Altay; Altemimi, Mohammed Fawzi; 20809
A dynamic beam shaping method is proposed for the generation of flat-top beams (FTBs) in the far field. Using the mixed-region amplitude freedom algorithm, this new method is used to design the required phase distribution encoded on a spatial light modulator for the generation of FTB profiles. The characteristics of these new beam shaping methods are used as beam parameters, such as the laser beam size, the beam intensity of square FTBs, and the root-mean-square error (RMSE). Using our proposed method, the theoretical performance of beam intensity shaping is improved to an RMSE < 0.02 with a minimum number of iterations of phase reconstruction. Using the phase hologram of dynamic beam shaping, theoretical and experimental comparisons of edge steepness and plateau uniformity were established for the square FTBs of variable beam sizes. It is shown that the dynamic beam shaping of FTBs can produce high intensity uniformity in the plateau region with steep edges, which makes it an effective tool, especially for laser machining applications.
Citation - WoS: 26
Citation - Scopus: 34
Effective damage mechanisms and performance evaluation of ceramic composite armors subjected to impact loading
(Sage Publications Ltd, 2014) Evci, Celal; Gülgeç, Müfit; Gulgec, Mufit; 243247; 4168
Researches on the armor systems composed of composite materials with ceramic frontal face and polymer-based back-support are continuously developing further. This study, which mainly covers the impact behavior of ceramic composite armors, is a two-stage research. The first stage involves the investigation of component-level impact characteristics and failure mechanisms of the ceramic composite armors. At this stage, low-velocity impact behavior of ceramics and fiber-reinforced composites is investigated. Impact test results revealed that impact loading is of dynamic nature and strength of the composite materials under dynamic loading increases considerably as a result of strain rate sensitivity, which makes them the right choice to be used in conjunction with ceramics in armor systems. The second stage examines the ballistic impact behavior and ballistic performance of the armor systems. The extent and pattern of impact damage related to projectile velocity are determined for the armor components and the armor itself.
Citation - WoS: 17
Citation - Scopus: 22
Experimental Investigation on Wire Electric Discharge Machining of Biodegradable AZ91 Mg Alloy
(Springer, 2021) Çoğun, Can; Urtekin, Levent; Ozerkan, Haci Bekir; Esen, Ziya; Cogun, Can; Genc, Asim; Esen, Ziya; Bozkurt, Fatih; 3837; 52373
The AZ91 magnesium alloy, used commonly as a biodegradable material in biomedical applications, is generally formed by conventional casting method (CCM) and high-pressure die casting method (HPDCM). The AZ91 alloys exhibit poor machinability with conventional chip removal methods since they degrade at elevated temperatures. In this study, the wire electric discharge machining (WEDM) was presented as a candidate process to machine the AZ91 alloy since no cutting stresses and plastic deformations were applied by the cutting tool to the part causing elevated temperatures. In this context, the WEDM machinability of the AZ91 alloy samples produced by cold chamber HPDCM and CCM at different process parameters, was experimentally investigated. The machining performance outputs (the machining current (I), the machining rate (MR), the average surface roughness (R-a), and surface topography) were found for the varying process parameters [pulse time (t(s)), pulse-off time (t(off)), dielectric flushing pressure (P-d), and wire speed (V-w)]. The present study revealed that the I and the MR were significantly dependent on the density, the porosity, and the micro structure of the samples, and the HPDCM samples gave the higher MR and the smoother surface than that of the CCM.
Citation - WoS: 6
Citation - Scopus: 7
Modeling distributed real-time systems in TIOA and UPPAAL
(Assoc Computing Machinery, 2016) Kartal, Yusuf Bora; Schmidt, Ece Guran; Schmidt, Klaus Werner; 17337
The mission- and life-critical properties of distributed real-time systems require concurrent modeling, analysis, and formal verification in the design stage. The timed input/output automata (TIOA) framework and the UPPAAL software package are two widely used modeling and verification tools for this purpose. To this end, we develop the algorithm TUConvert for converting distributed TIOA models to UPPAAL behavioral models and formally prove its correctness. We demonstrate the applicability of our algorithm by the formal verification of a distributed real-time industrial communication protocol that is modeled by TIOA.
Citation - WoS: 8
Citation - Scopus: 8
Reconfigurability of behavioural specifications for manufacturing systems
(Taylor & Francis Ltd, 2017) Schmidt, Klaus Werner
Reconfigurable manufacturing systems (RMS) support flexibility in the product variety and the configuration of the manufacturing system itself in order to enable quick adjustments to new products and production requirements. As a consequence, an essential feature of RMS is their ability to rapidly modify the control strategy during run-time. In this paper, the particular problem of changing the specified operation of a RMS, whose logical behaviour is modelled as a finite state automaton, is addressed. The notion of reconfigurability of specifications (RoS) is introduced and it is shown that the stated reconfiguration problem can be formulated as a controlled language convergence problem. In addition, algorithms for the verification of RoS and the construction of a reconfiguration supervisor are proposed. The supervisor is realised in a modular way which facilitates the extension by new configurations. Finally, it is shown that a supremal nonblocking and controllable strict subautomaton of the plant automaton that fulfils RoS exists in case RoS is violated for the plant automaton itself and an algorithm for the computation of this strict subautomaton is presented. The developed concepts and results are illustrated by a manufacturing cell example.
Citation - WoS: 2
Citation - Scopus: 3
Window length insensitive real-time EMG hand gesture classification using entropy calculated from globally parsed histograms
(Sage Publications Ltd, 2023) Algüner, Ayber Eray; Alguner, Ayber Eray; Ergezer, Halit; Ergezer, Halit; 293396
Electromyography (EMG) signal classification is vital to diagnose musculoskeletal abnormalities and control devices by motion intention detection. Machine learning assists both areas by classifying conditions or motion intentions. This paper proposes a novel window length insensitive EMG classification method utilizing the Entropy feature. The main goal of this study is to show that entropy can be used as the only feature for fast real-time classification of EMG signals of hand gestures. The main goal of this study is to show that entropy can be used as the only feature for fast real-time classification of EMG signals of hand gestures. Additionally, the entropy feature can classify feature vectors of different sliding window lengths without including them in the training data. Many kinds of entropy feature succeeded in electroencephalography (EEG) and electrocardiography (ECG) classification research. However, to the best of our knowledge, the Entropy Feature proposed by Shannon stays untested for EMG classification to this day. All the machine learning models are tested on datasets NinaPro DB5 and the newly collected SingleMyo. As an initial analysis to test the entropy feature, classic Machine Learning (ML) models are trained on the NinaPro DB5 dataset. This stage showed that except for the K Nearest Neighbor (kNN) with high inference time, Support Vector Machines (SVM) gave the best validation accuracy. Later, SVM models trained with feature vectors created by 1 s (200 samples) sliding windows are tested on feature vectors created by 250 ms (50 samples) to 1500 ms (300 samples) sliding windows. This experiment resulted in slight accuracy differences through changing window length, indicating that the Entropy feature is insensitive to this parameter. Lastly, Locally Parsed Histogram (LPH), typical in standard entropy functions, makes learning hard for ML methods. Globally Parsed Histogram (GPH) was proposed, and classification accuracy increased from 60.35% to 89.06% while window length insensitivity is preserved. This study shows that Shannon's entropy is a compelling feature with low window length sensitivity for EMG hand gesture classification. The effect of the GPH approach against an easy-to-make mistake LPH is shown. A real-time classification algorithm for the entropy features is tested on the newly created SingleMyo dataset.

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