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The majority of power system faults occur in transmission lines. The classification of these faults in power systems is an important issue. In this paper, the real parameters of a 28 km, 154 kV transmission line between Simav and Demirci in Turkey's electricity transmission network is simulated in MATLAB/Simulink. Wavelet packet transform (WPT) is applied to instantaneous voltage signals. Instantaneous active power components are obtained by multiplying instantaneous currents obtained from a voltage source side with these WPT-based voltage signal components. A new feature vector extraction scheme is employed by calculating the energies of instantaneous active power components.Constructed feature vectors are treated with a classifier for short-circuit faults that occurred in high-voltage energy transmission lines; this is known as the common vector approach (CVA). This is the first implementation of CVA in the classification of short-circuit faults that occurred in high-voltage energy transmission lines. Furthermore, the same feature vector is applied to a support vector machine and artificial neural network for a comparison with the CVA method regarding classification performance and testing duration issues. Additionally, a graphical user interface is designed in MATLAB/GUI. Various noise levels, source frequencies, fault distances, fault inception angles, and fault exposure durations can be investigated with this interface. Classification of short-circuit faults in high-voltage transmission line is achieved by using an offline monitoring methodology. It is concluded that a combination of the proposed feature extraction scheme with the CVA classifier gives substantially high performance for the classification of short circuit faults in transmission line.

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Reverse engineering methods are important for remodeling or measuring damaged or non-damaged parts. Reverse engineering also enables the design of complex components, reducing actual product production time and prototype production time. With this method, damaged gear wheels can be modeled in a short time due to the regular geometry and symmetrical properties of the teeth and it is real models can be produced. In this study, the damaged motor cam gear was scanned with a three dimensional (3D) scanner and a mesh model was formed. Then, solid model of part was created and genuine prototype was produced with 3D printer. The deviations of geometric dimensions between the mesh model and the solid model were analyzed and the levels of convergence were determined. The three-dimensional prototyping method provides great convenience for the designer due to it gives quick feedback in product development process. At the end of the study, geometric values between solid model and prototype model were compared and deviations from actual value were determined.