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Power Transformers INTRODUCTION OF POWER TRANSFORMER They have rating above 200 kva and used in generating station and substation used for power transmission line for stepping up and stepping down the voltage. They may be either single phase or three phase unit. CONTENTS INTRODUCTION OF POWER TRANSFORMER TYPES OF TRANSFORMER TRANSFORMER FAULTS EQIPMENTS USED FOR THE PROTECTION OF POWER TRANSFORMER Artificial Neural Network Neural network design ADVANTAGE CONCLUSION TYPES OF TRANSFORMER Power transformer. Distribution transformer. DETAILS OF POWER TRANSFORMER 12500/10000 KVA. 50 hz. 132 kv (H.v. side) 6.9 kv (L.v. side) 54.7 amp (H.v. side) 1045.39 amp (L.v. side) 55 degree centigrade (max temp rise) 14706/17100 Liter (oil) TRANSFORMER FAULTS Transformer faults are generally classified in to five categories: Winding and terminal faults Core faults Tank and transformer accessory faults On-load tap changer faults Abnormal operation conditions Sustained or uncleared external faults DAMAGE ON TRANSFORMER EQIPMENTS USED FOR THE PROTECTION OF POWER TRANSFORMER Lightning Arrester. Over Current Relay. Buchloz relay. Earth fault relay. Oil level indicator. Over fluxing relay. Artificial Neural Network An artificial neural network (ANN) is an imitation of human neural network An ANN is constructed by layers of simulated artificial neurons. An artificial neuron is a simulation of real neuron Artificial neural networks Output Inputs An artificial neural network is composed of many artificial neurons that are linked together according to a specific network architecture. The objective of the neural network is to transform the inputs into meaningful outputs. Neural network design The neural network consists of two cell types: weight cells and output cells. Weight cells act as light filters, and the output cells act as reporters. The two cell types are used together to program a desired output from a set input. ADVANTAGE OF NEURAL NETWORK · pattern classification · regularity detection · image processing · speech analysis · optimization problems · robot steering · quality assurance CONCLUSION According to the approximation ability of neural network, constructing the neural network model replacing the physical transformer model.
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