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Full-Text Articles in Physical Sciences and Mathematics
Group Control And Identification Of Residential Appliances Using A Nonintrusive Method, Sunil Semwal, Munendra Singh, Rai Sachindra Prasad
Group Control And Identification Of Residential Appliances Using A Nonintrusive Method, Sunil Semwal, Munendra Singh, Rai Sachindra Prasad
Turkish Journal of Electrical Engineering and Computer Sciences
Identifying and controlling (ON/OFF) electrical appliance(s) from a remote location is an essential part of energy management. This motivated us to design a system that can collect the aggregate load signature from a single point, obtain the features, and finally identify the ON state of electrical appliance(s). The proposed disaggregation technique can be divided into two modules: the first part proposes an electrical installation system to disaggregate the appliance at the circuit level, whereas the second part consists of feature selection, dimension reduction, and classification algorithms. Load signatures of electrical appliances were combined with white Gaussian noise to analyze how …
A Real-Time American Sign Language Word Recognition System Based On Neural Networks And A Probabilistic Model, Neelesh Sarawate, Ming Chan. Leu, Cemi̇l Öz
A Real-Time American Sign Language Word Recognition System Based On Neural Networks And A Probabilistic Model, Neelesh Sarawate, Ming Chan. Leu, Cemi̇l Öz
Turkish Journal of Electrical Engineering and Computer Sciences
The development of an American Sign Language (ASL) word recognition system based on neural networks and a probabilistic model is presented. We use a CyberGlove and a Flock of Birds motion tracker to extract the gesture data. The finger joint angle data obtained from the sensory glove defines the handshape while the data from the motion tracker describes the trajectory of the hand movement. The four gesture features, namely handshape, hand position, hand orientation, and hand movement, are recognized using different functions that include backpropagation neural networks. The sequence of these features is used to generate a specific sign or …
Performance Of Support Vector Regression Machines On Determining The Magnetic Characteristics Of The E-Core Transverse Flux Machine, Çi̇ğdem Gündoğan Türker, Feri̇ha Erfan Kuyumcu, Nurhan Türker Tokan
Performance Of Support Vector Regression Machines On Determining The Magnetic Characteristics Of The E-Core Transverse Flux Machine, Çi̇ğdem Gündoğan Türker, Feri̇ha Erfan Kuyumcu, Nurhan Türker Tokan
Turkish Journal of Electrical Engineering and Computer Sciences
The E-core transverse flux machine (ETFM) has major advantages with its different and unique structure in conventional electrical machines. It is a combination of transverse flux and reluctance principle. In this work, support vector regression machines (SVRMs) are used to obtain the magnetic characteristic parameters of the ETFM for the first time and it is compared with its artificial neural network model. The data for the training and testing of the SVRMs are obtained from experimental measurements. It is proven that SVRMs can conveniently be used in the modeling of the magnetic behaviors of highly nonlinear ETFM with better accuracy …
Mechanical Fault Detection In Permanent Magnet Synchronous Motors Using Equal Width Discretization-Based Probability Distribution And A Neural Network Model, Mehmet Akar, Mahmut Heki̇m, Umut Orhan
Mechanical Fault Detection In Permanent Magnet Synchronous Motors Using Equal Width Discretization-Based Probability Distribution And A Neural Network Model, Mehmet Akar, Mahmut Heki̇m, Umut Orhan
Turkish Journal of Electrical Engineering and Computer Sciences
This paper focuses on detecting the static eccentricity and bearing faults of a permanent magnet synchronous motor (PMSM) using probability distributions based on equal width discretization (EWD) and a multilayer perceptron neural network (MLPNN) model. In order to achieve this, the PMSM stator current values were measured in the cases of healthy, static eccentricity, and bearing faults for the conditions of three speeds and five loads. The data was discretized into several ranges through the EWD method, the probability distributions were computed according to the number of current values belonging to each range, and these distributions were then used as …