Master Degree / Yüksek Lisans Tezleri

Permanent URI for this collectionhttps://hdl.handle.net/11147/3008

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Author: search.filters.author.Özdemir, SerhanPublisher: search.filters.publisher.Izmir Institute of Technology

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Now showing 1 - 7 of 7
  • Master Thesis
    Microscale Precise Position Measurement and Monitoring of Sliding Valves
    (Izmir Institute of Technology, 2019) Özdemir, Serhan; Özdemir, Serhan; Özdemir, Serhan; 03.10. Department of Mechanical Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    In present study, a sensor, Accuciser, is presented to know the position of sliding valves which have ferromagnetic or diamagnetic guide. The main objective is to develop a sensor, which has low cost and high resolution, that measures the displacement of engine valves or SCR injectors which are used in especially in the automotive industry. For now, the position of the valves, which are using in propulsion systems, or SCR injector cannot be known with a signal from an analog sensor. Instead of analog sensor, the mapping is used from experimental data. However, this mapping gives inaccurate results due to driving style or usage of the system. After seeing the gap in these systems, the sensor was developed, and it fulfils this gap. The sensor is developed based on Faraday’s Law of Induction which was discovered by Michael Faraday in 1830. The sensor consists of two coils and one coil located on top of the other. The most important property of the proposed sensor is working with a direct current. In fact, if the valve is actuated by an electromagnetic force, there is no power consumption on the sensor. The experimental results, for the latter property, are corroborated by theoretical calculations. The output of the sensor is directly proportional to the displacement of the core and it has high signal-to-noise ratio because of the nature of magnetism. The results show that using Accuciser, the proposed sensor, to monitor valve displacement gives more reliable results than current technology.
  • Master Thesis
    Sub-Kilowatt, Efficient Capacitive Power and Data Transfer for Monitoring the Major Mechanical Variables
    (Izmir Institute of Technology, 2019) Karabulut, Abtulgalip; Özdemir, Serhan; Özdemir, Serhan; 03.10. Department of Mechanical Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    The main aim of this thesis is to design and prototype a sub-kilowatt, efficient capacitive data and power transfer (CPT) system that for example, monitors the loads on an axle of a vehicle. The data and power are transmitted wirelessly. In a separate case study, the power is provided for the weight measurement system by an E class power amplifier. In the industry, today, wireless power and data transfer methods have become quite popular. Some of those methods are inductive power transfer (IPT), capacitive power transfer, micro-wave power transfer (MCP). One of these techniques, which is the theme of this thesis, is the capacitive power and data transfer. The capacitive power system is quite compact and does not create electromagnetic interference (EMI), which is one of the strengths of the CPT. Hence, the stability of the embedded electronics system is preserved. Another attractive feature of CPT is that data and power can be transferred at the same frequency over a short distance. This thesis addresses the various facets of the CPT system. The historical development of the CPT technique has started with Nicola Tesla. Wireless power transfer methodology could safely be attributed to him. The system consists of two main parts which are the weight measurement system and power transmitting system. The power is transferred by the copper capacitive plates with 100 cm2 surface area. Average error of the measurement system is computed as 1.1% with high signal-to-noise ratio (SNR). Finally, the capacitive power and data transfer system has been designed with 83.8% efficiency at 1.7 MHz frequency and high SNR.
  • Master Thesis
    Data Driven Modeling Using Reinforcement Learning in Autonomous Agents
    (Izmir Institute of Technology, 2003) Karakurt, Murat; Özdemir, Serhan; Özdemir, Serhan; 03.10. Department of Mechanical Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    This research has aspired to build a system which is capable of solving problems by means of its past experience, especially an autonomous agent that can learn from trial and error sequences. To achieve this, connectionist neural network architectures are combined with the reinforcement learning methods. And the credit assignment problem in multi layer perceptron (MLP) architectures is altered. In classical credit assignment problems, actual output of the system and the previously known data in which the system tries to approximate are compared and the discrepancy between them is attempted to be minimized. However, temporal difference credit assignment depends on the temporary successive outputs. By this new method, it is more feasible to find the relation between each event rather than their consequences.Also in this thesis k-means algorithm is modified. Moreover MLP architectures is written in C++ environment, like Backpropagation, Radial Basis Function Networks, Radial Basis Function Link Net, Self-organized neural network, k-means algorithm.And with their combination for the Reinforcement learning, temporal difference learning, and Q-learning architectures were realized, all these algorithms are simulated, and these simulations are created in C++ environment.As a result, reinforcement learning methods used have two main disadvantages during the process of creating autonomous agent. Firstly its training time is too long, and too many input parameters are needed to train the system. Hence it is seen that hardware implementation is not feasible yet. Further research is considered necessary.
  • Master Thesis
    An Investigation With Fractial Geometry Analysis of Time Series
    (Izmir Institute of Technology, 2005) Kaya, Aysun; Özdemir, Serhan; Özdemir, Serhan; 03.10. Department of Mechanical Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    In this thesis, three kinds of fractal dimensions, correlation dimension, Hausdorff dimension and box-counting dimension were used to examine time series. To demonstrate the universality of the method, ECG (Electrocardiogram) time series were chosen. The ECG signals consisted of ECGs of three persons in four states for two applications. States are normal, walk, rapid walk and run. These three people are selected from the same age, and height group to minimize variations. First application was made for approximately 1000 samples of size of ECG signals and the second for the whole of the measured ECG signals. Fractal dimension measurements under different conditions were carried out to find out whether these dimensions could discriminate the states under question. A total of 24 ECG signals were measured to determine their corresponding fractal dimensions through the above-mentioned methods. It was expected that fractal dimension values would indicate the states related to the different activities of the persons. Results show that no direct link was found connecting a certain dimension to a certain activity in a consistent manner. Furthermore, no congruence was also found among the three dimensions that were employed. According to these results, it can be stated that fractal dimension values on their own may not be sufficient to identify distinct cases hidden in time series. Time series analysis may be facilitated when additional tools and methods are utilized as well as fractal dimensions at detecting telltale signs in signals of different states.
  • Master Thesis
    The Control of a Manipulator Using Cerebellar Model Articulation Controllers
    (Izmir Institute of Technology, 2003) Darka, Murat; Özdemir, Serhan; Özdemir, Serhan; 03.10. Department of Mechanical Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    The emergence of the theory of artificial neural networks has made it possible to develop neural learning schemes that can be used to obtain alternative solutions to complex problems such as inverse kinematic control for robotic systems. The cerebellar model articulation controller (CMAC) is a neural network topology commonly used in the field of robotic control which was formulated in the 1970s by Albus. In this thesis, CMAC neural networks are analyzed in detail. Optimum network parameters and training techniques are discussed. The relationship between CMAC network parameters and training techniques are presented. An appropriate CMAC network is designed for the inverse kinematic control of a two-link robot manipulator.
  • Master Thesis
    Contrast Enhancement by Lateral Inhibition in a Sensory Network
    (Izmir Institute of Technology, 2006) Coşkun, Anıl; Özdemir, Serhan; Özdemir, Serhan; 03.10. Department of Mechanical Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    The most important mechanism to occur in biological distributed sensory networks (DSNs) is called "Lateral Inhibition, (L.I.)". L.I. relies on one simple principle. Each sensor strives to suppress its neighbors in proportion to its own excitation. L.I. is found all around the human nervous and sensory system. In audition, for example lateral inhibition occurs at the relay points on the way up to the brain. It is realized that L.I. must not be limited to biosystems. Any artificial system claiming to have a discriminating tactile sensing, say like a robotic hand, ought to carry a redundancy reduction and contrast enhancement tool similar to L.I.In this study, lateral inhibition mechanism was analyzed and simulated.To simulate the LI. mechanism an experimental set-up was built up.The effects of LI. mechanism were observed in an artificial sensory network that contained photodiodes.The sensors in the networks were stimulated by a halogen light source that can be moved in three axes.The results showed that LI. is not only functional for biological DSNs but also for artificial DSNs.LI. mechanism was also used to localize an unknown position of light source that illuminated the photosensitive sensory network containing high and low quality sensors. Each photosensitive sensor was calibrated relative to the distance to the light source. The output of each sensor was converted into a distance reading according to the calibration and this was employed to localize the position of the light source. Results showed that lateral inhibition mechanism increased the sensitivity of localization and it gave an ability to low quality sensors to make localization as sensitive as high quality sensors.
  • Master Thesis
    On the Predictability of Time Series by Metric Entropy
    (Izmir Institute of Technology, 2006) Sevil, Hakkı Erhan; Özdemir, Serhan; Özdemir, Serhan; 03.10. Department of Mechanical Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    The computation of the metric entropy, a measure of the loss of information along the attractor, from experimental time series is the main objective of this study. In this study, replacing the current warning systems (simple threshold based, on/off circuits), a new and promising prognosis system is tried to be achieved by the metric entropy, i.e. Kolmogorov . Sinai entropy, from chaotic time series. Additional to metric entropy, correlation dimension and time series statistical parameters were investigated.Condition monitoring of ball bearings and drill bits was achieved in the light of practical considerations of time series applications. Two different accelerated bearing run-to-failure test rigs were constructed and the prediction tests were performed.However, as a reason of shaft failure in both structures during the experiments, none of them is completed. Finally, drill bit breakage experiments were carried out. In the experiments, 10 small drill bits (1 mm ) were tested until they broke down, while vibration data were consecutively taken in equal time intervals. After the analysis, a consistent decrement in variation of metric entropy just before the breakage was observed. As a result of the experiment results, metric entropy variation could be proposed as an early warning system.