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Öğe Bir Asenkron Motorun Mekanik Titreşim Sinyallerinin Ölçülerek Arıza Analizinin Yapılması(Osman SAĞDIÇ, 2020) Çeven, Süleyman; Bayır, RaifAsenkron motorlar, endüstride en yaygın kullanılan motor türüdür. Asenkron motorların verimlerinde meydana gelen bozulmalar, çalışma performanslarını ciddi şekilde etkilemektedir. Üretim sürecinin aksamaması için bu motorların bakımlarının periyodik bir şekilde yapılması ve durumlarının izlenmesi gerekmektedir. Bu çalışmada bir asenkron motorun farklı hız kademelerinde mekanik titreşimlerinin ölçülmesi için bir deney düzeneği tasarlanmış ve gerçekleştirilmiştir. Deney düzeneğinde asenkron motorun gövdesine "Z" ekseni yönünde bağlanan bir ivmeölçer yardımıyla titreşim sinyalleri elektrik sinyaline dönüştürülmüş ve bir veri alışveriş kartı üzerinden bilgisayar ortamına aktarılmıştır. Bu yöntem ile asenkron motorda gerçek zamanlı durum izleme gerçekleştirilmektedir. Motor üzerinde oluşan mekanik titreşimler ayrıca titreşim ölçümü yapabilen test cihazı ile ölçülmüş ve hafıza kartına kayıt edilmiştir. Elde edilen sensör verileri FFT dönüşümü kullanılarak analiz edilmiş ve sonuçlar yorumlanmıştır.Öğe Developing Filter to Separate Human Voice from Ambient Sound(Osman SAĞDIÇ, 2020) Çeven, Süleyman; Bayır, RaifIn this study, it is aimed to reveal the sound signals of the lathe operator by filtering them from outside sounds and clarify the sound signals in a production plant that produces machining in the industrial environment. In the study, the audio signals of the speech of the lathe operator were recorded with the help of a microphone. On the recorded speech audio signals, lathe and ambient audio signals were created in Matlab environment and added. In Matlab environment, noisy sound signal simulation that includes operator and environment sounds is made. FFT operation was performed on the noisy sound signal and frequency spectra of operator sound and other ambient sounds were observed. Frequency wavelengths of noisy signals were determined in the simulated audio signal. Outside sounds are filtered using the FIR band stop filter and low pass filter from the noisy sound signal and the operator sound is obtained clearly.Öğe Development of IoT Based Battery Management System(Ieee, 2021) Çeven, Süleyman; Küçükkülahli, Enver; Albayrak, Ahmet; Biçen, YunusIn this study, the modular battery management system used in electric vehicles was developed and monitored with the IoT-based MQTT protocol. In recent years, electric vehicles have been widely studied by researchers and long-lasting battery systems have been developed. In this study, a modular battery management system that performs the charging process with the passive balancing method has been developed. The battery has been developed for electric vehicles with more than 1 kWh of energy. There is temperature, current and voltage sensors at each node for battery management. A temperature sensor has been added to the system in case of overheating of the battery. The data collected over the battery is transferred to the web environment with MQTT, one of the IoT protocols. Passive balancing is preferred for balancing the batteries during charging. During charging, the MQTT server notifies the network to set the required voltage for each node.Öğe Hardware-in-the-Loop Based State of Charge Estimation for Li-Ion Batteries using Multilayer Perceptron(2020) Çeven, Süleyman; Bayır, RaifIn this study, hardware-in-the-loop based real-time state of charge estimation was performed in Li-Ion batteries, which are widely used in hybrid and battery electric vehicles. The state of charge is estimated on the Li-Ion battery cell that forms the electric vehicle battery system. Multi-layer perceptron approach has been preferred as a method for estimating the battery state of charge. Discharge experiments based on different electrical loads were applied to the Li-Ion battery cell to be used in multilayer perceptron learning processes. An experimental setup has been prepared to perform the discharge process under different electrical loads. In each discharge experiment, battery open circuit voltage, battery discharge current and battery cell temperature parameters were measured and were recorded. By using the data obtained from the experiments on the battery cell, a multilayer perceptron model was created in MATLAB environment. After creating the multilayer perceptron model, the real-time battery state of charge the was estimated at different discharge currents in the experimental setup and the results obtained were evaluated.Öğe Modelling of PID and LQR Controller for Stability and Position Control in Double Inverted Pendulum System(Osman SAĞDIÇ, 2020) Çeven, Süleyman; Albayrak, AhmetNowadays, stability of the inverted pendulum system is an up-to-date topic in which researchers working on control systems compare control theories and methods. The inverse pendulum systems are unstable and nonlinear systems in terms of controllability. Due to the complexity of the structure and the difficulty of the control process, many advanced control theories can be applied on these systems to improving the performance of the controllers. In this study, PID and LQR controller methods were applied on a double inverted pendulum modeled in MATLAB environment and their controller performances were compared. The results via experimental studies were evaluated on the applicability of PID and LQR control methods.Öğe Real-time range estimation in electric vehicles using fuzzy logic classifier(Elsevier Ltd, 2020) Çeven, Süleyman; Albayrak, Ahmet; Bayır, RaifNowadays, many scientists and companies in the automotive sector in the world are undertaking many important studies on electric vehicle technologies. For the electric vehicle to function as desired, the subsystems of the vehicle must be monitored and the parameters related to the vehicle must be kept in the most efficient range. Efficient use of these systems in electric vehicle will increase the vehicle range, as well as ensure the long life of the components used in the vehicle subsystems. Today, problem areas such as calculating the range of electric vehicles and battery state of charge have not yet been sufficiently standardized. The aim of this study is to make a range estimation in electric vehicle with fuzzy logic classifier which has been successfully applied in various problem areas. The fuzzy logic classifier is designed for range estimation, which is one of the most important research areas of electric vehicles today. In the Mamdani type fuzzy logic approach, dynamic vehicle parameters are taken into consideration. The fuzzy logic classifier considers the battery parameters of the vehicle and the power consumed instantly. In the prediction system, the power spent on the vehicle and the battery charge status are selected as inputs. The developed system was evaluated with three different test scenarios on the same track. These tests were conducted with no load (driver only), half load (driver + one person) and fully load (driver + three persons). The fuzzy logic classifier system determines in real-time how far electric vehicle can travel. © 2020 Elsevier Ltd
