Mukden Ugur

Analyzing and modeling the 2D surface tracking patterns of polymeric insulation materials

The structure and topography of surface tracking patterns generated on the surface of unfilled and filled samples of polyester resin using the international standard procedure (IEC 587, Inclined-plane Tracking Test) have been studied. The effect of contaminant flow rate, applied voltage and the percentage content of particulate zinc oxide on tracking behavior has been determined. Three alternative mathematical algorithms have been used to establish the fractal dimensions of the tracking patterns as a function of the above three parameters. To model the surface tracking patterns,two methods have been applied. Firstly, a resistive network has been used in which the insulator surface is assumed to consist of imaginary vertically and horizontally placed resistors. This model is capable of producing several types of trees observed in insulating materials. However, the surface tracking patterns are mostly unbranched and it is not possible to produce realistic images with this model. The second method, Brownian motion, is mainly a recursive technique and does not take Laplacian field values into account. The resolution of the images is high, hence the simulated patterns are almost indistinguishable from the real images.

Analysing the 2-D surface tracking patterns by using cellular neural networks

Surface tracking is one of the major breakdown mechanisms observed on polymeric outdoor insulators. Continuous discharges on the surface of the insulator cause hot spots on certain points, which finally lead to carbonised tracking paths crossing the surface between the high voltage and earth electrodes. This paths (patterns) are greatly influenced in size and shape by the external environmental conditions. The lifetime of an insulator can be increased by cleaning up its contaminated surface before a total breakdown occurs. However in most cases we do not know exactly which of the environmental factors reduced the service life of the insulator. In this study, polyester resin based insulators are investigated and the results are evaluated using Cellular Neural Network (CNN) approaches. CNN is an analog parallel computing paradigm defined in space and characterized by locally connection between processing elements. CNN with a complex dynamic behaviour have found interesting applications in image processing and pattern recognition. Since CNN proved to be an effective way in categorising different tracking patterns, using this approach we will be able to determine the environmental conditions which. The insulators experienced throughout their service life. At the end this can help us to design our insulator specifically for a certain location, and hence increase the useful lifetime of the insulator.

Modeling and Suppression of Chaotic Ferroresonance in a Power System by Using Memristor-based System

Abstract Power systems contain capacitances and inductances that can initiate chaotic ferroresonance due to the non-linear operating characteristics of ferromagnetic materials, such as power transformer cores. Chaotic ferroresonance is a highly disturbing complex, non-linear phenomenon that may cause over-voltages and over-currents; hence, it can compromise regular system operation. The memristor is a non-linear passive two-terminal electricalcomponent, foreseen and introduced as the fourth ideal circuit element. In this studys novel approach, a memristive system is proposed for modeling chaotic ferroresonance in power systems. Employing the memristive circuit as the source of ferroresonance, flexible and adjustable solutions of the dynamic system can be obtained easily. The chaotic characteristic of the proposed system is verified by using a bifurcation diagram and Lyapunov exponent analysis. To reduce the effects of chaotic ferroresonance, a memristor-based system is proposed for damping chaotic oscillations of the system as a protection element. simulation program with integrated circuit emphasis (SPICE) simulations have been carried out for the performance analysis of the proposed system during ferroresonance, and suppression modes are presented.

A quantitative skin impedance test to diagnose spinal cord injury

The purpose of this study was to develop a quantitative skin impedance test that could be used to diagnose spinal cord injury (SCI) if any, especially in unconscious and/or non-cooperative SCI patients. To achieve this goal, initially skin impedance of the sensory key points of the dermatomes (between C3 and S1 bilaterally) was measured in 15 traumatic SCI patients (13 paraplegics and 2 tetraplegics) and 15 control subjects. In order to classify impedance values and to observe whether there would be a significant difference between patient and subject impedances, an artificial neural network (ANN) with back-propagation algorithm was employed. Validation results of the ANN showed promising performance. It could classify traumatic SCI patients with a success rate of 73%. By assessing the experimental protocols and the validation results, the proposed method seemed to be a simple, objective, quantitative, non-invasive and non-expensive way of assessing SCI in such patients.

Investigation the effect of environmental factors on the performance of polymeric outdoor insulation

Surface tracking is one of the severe degradation mechanisms observed on polymeric insulators. There are too many factors associated with the degradation process, hence it is not easy to make an estimate about the useful service life of an insulator. However it is possible to reduce the variability observed in the tracking initiation times and tracking patterns by testing the samples in laboratory under predefined conditions (4 kV applied voltage and 36 ml/h flow rate of liquid). In this study, by using the ASTM D 2303 Inclined Plane Tracking Test method the effects of longitudinal compressive and tensile stress, ultraviolet (UV) radiation and wind pressure from different positions with respect to the surface of the sample under test have been investigated in detail. All samples have been prepared by using polyester resin without any accelerator. In all cases tracking initiation times were reduced significantly depending on the external conditions. UV radiation and wind pressure caused bushy type carbonised tracking patterns with wide branches around the high voltage electrode.

Comparison of the Data Classification Approaches to Diagnose Spinal Cord Injury

In our previous study, we have demonstrated that analyzing the skin impedances measured along the key points of the dermatomes might be a useful supplementary technique to enhance the diagnosis of spinal cord injury (SCI), especially for unconscious and noncooperative patients. Initially, in order to distinguish between the skin impedances of control group and patients, artificial neural networks (ANNs) were used as the main data classification approach. However, in the present study, we have proposed two more data classification approaches, that is, support vector machine (SVM) and hierarchical cluster tree analysis (HCTA), which improved the classification rate and also the overall performance. A comparison of the performance of these three methods in classifying traumatic SCI patients and controls was presented. The classification results indicated that dendrogram analysis based on HCTA algorithm and SVM achieved higher recognition accuracies compared to ANN. HCTA and SVM algorithms improved the classification rate and also the overall performance of SCI diagnosis.

The effect of colemanite on dielectric properties of polymers

The aim of this study is to investigate the effect of colemanite on dielectric properties of polymers. In this study polyester is used as the base polymer insulator. The electrical conductivity, relative permittivity and dissipation factor (tan¿) of polymers are measured as a function of colemanite concentration in polyester samples. After dielectric measurements are completed, breakdown strengths are evaluated for each concentration. Experimental measurements show that adding colemanite to polyester has an influence for good in samples which is going to be used in electrical applications.

Improvement of flame retardant properties in polyester insulators

In this study the effect of boron concentrations on tracking and erosion resistance of polyesters has been investigated. Samples with different boron concentrations were tested in an inclined plane tracking test apparatus. The results indicate that lower concentrations (0.1%-0.2%) of boron prevents the formation of free carbon over the surface of the composite samples and hence the specimens are mostly damaged by the erosion of the surface. However by increasing the boron quantity (0.4%-0.6%) in polyester samples, the tendency of the resulting composites changes again and samples are mostly damaged by surface tracking rather than erosion.

Dedection of eye-blink movements with sensors

During the lifetime, one of the most involuntary or voluntary movements of the human body is blinking eyes. The main purpose of ongoing scientific researches is to obtain a meaningful and fundamental data by observing eye blink movement, which might give some valuable information for other research subjects. Eye blink data is being frequently analyzed and processed for different application fields such as wearable technologies, intelligent driver warning systems, etc. In this study, eye blink data is obtained as biomechanical outcome for application of biomedical purposes in treatment of diseases caused by eye blink complications. The motivation of the study is based on facial paralysis disease, which may be resulted in eye blink difficulty especially in one eye. The proposed treatment system operates by triggering eyelid muscles by an appropriate synchronizing data obtained by healthy eye blink movements. The synchronizing data is acquired by using QRD1114 sensor module which contains IR led and phototransistör. The proposed system with its ergonomic structure does not block the angle of vision.

Analysis of Transformer Resonant Overvoltages Due to Switching Capacitance

Power transformer transients, which are originated from non-linear operating characteristics, may cause failure of a power system. In this study, a special resonance phenomenon where overvoltages observed due to switching capacitances of the line is investigated. This situation is detected while high voltage side of the transformer is open circuit (no-load) and the low voltage side is connected to a transmission line through nonlinear switch (or breaker). This special resonance is caused by the interaction of leakage inductance of the transformer windings and the switching capacitance. A test setup containing 220V/34.5kV transformer is employed for realization of simulation results obtained by SPICE analysis. In order to simulate switching capacitance, a capacitance of 5.54μF is connected to low voltage side. The recorded and simulated test results show good correspondence. Observed overvoltages are analysed by continuous wavelet transform (CWT) and fast Fourier transform (FFT) techniques. Also the energy distribution, which is generated by overvoltages, is investigated by instantaneous energy levels. Keywords—switching capacity, power transformer, overvoltage, continuous wavelet transform, resonance