scholarly journals Distance Protection Scheme For Protection of Long Transmission Line Considering the Effect of Fault Resistance By Using the ANN Approach

2013 ◽  
pp. 231-235
Author(s):  
Anil Vaidya ◽  
Prasad A. Venikar
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Artificial Neural Network ◽  
Transmission Line ◽  
Transmission Lines ◽  
Distance Protection ◽  
New Approach ◽  
Protection Scheme ◽  
Fault Resistance ◽  
Artificial Neural Network Ann

Traditional electromechanical distance relays used for protection of transmission lines are prone to effects of fault resistance. Each fault condition corresponds to a particular pattern. So use of a pattern recognizer can improve the relay performance. This paper presents a new approach, known as artificial neural network (ANN) to overcome the effect of fault resistance on relay mal-operation. This method is based on pattern recognition and classification. The scheme utilizes the magnitudes of resistance and reactance as inputs. Once trained with a large number of patterns corresponding to various conditions, it can classify unknown patterns. It also has the advantage that it can adapt itself with the changing network conditions.

scholarly journals WT-ANN based fault discrimination for transmission system

2018 ◽  
Vol 7 (1.8) ◽  
pp. 144
Author(s):  
P Venkata Lakshmi ◽  
P N. S. Poojitha ◽  
Y Srinivasrao
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Wavelet Transform ◽  
Power System ◽  
Transmission Line ◽  
Transmission Lines ◽  
Power Supply ◽  
Protection Scheme ◽  
Efficient Protection ◽  
Continuous Power

Protection of transmission line is a complex in power system as the majority of the faults in power system are transmission faults. A proper protection is needed for transmission line for continuous power supply. To provide a strong as well as an efficient protection scheme, in this paper we are using wavelet technique and artificial neural network. By using these mentioned two techniques we can detect the faults in transmission line and also, we can classify the detected faults. Wavelet transform has strong mathematical, very fast and accurate tools for brief signal inside the transmission lines and synthetic neural network can make a unique between measured sign and associated signal that has different pattern. 

Experimenting with Recognition Accelerator for Pavement Distress Identification

1996 ◽  
Vol 1536 (1) ◽  
pp. 130-135 ◽  
Author(s):  
Sudhakar Nallamothu ◽  
Kelvin C. P. Wang
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Artificial Neural Network ◽  
Coulomb Energy ◽  
Processing Unit ◽  
Basic Principles ◽  
Pavement Distress ◽  
The Core ◽  
Artificial Neural Network Ann ◽  
Computer Board

A study was conducted using a computer board embedded with an artificial neural network (ANN) microchip for pattern recognition of pavement distress classification. The basic principles behind ANNs and pattern recognition are discussed. The hardware architecture of the Ni1000 recognition accelerator chip, which is the core of the ANN computer board, is presented, and the principle of operation of the restricted coulomb energy algorithm used in the chip is discussed. It is demonstrated that the Ni1000 Recognition Accelerator chip can be used for pattern recognition of pavement distress. Distresses in pavement images have been successfully classified using the Ni1000 recognition accelerator. The Ni1000 has the potential to be used as the core processing unit for distress classification at highway speeds.

Study on the Effectiveness Evaluation of the Weapon Equipment Based on Artificial Neural Network

2014 ◽  
Vol 926-930 ◽  
pp. 3262-3265
Author(s):  
Feng Gao ◽  
Fei Song ◽  
Guo Qing Huang ◽  
Mao Yang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Bp Neural Network ◽  
Learning Algorithm ◽  
Effectiveness Evaluation ◽  
Matlab Toolbox ◽  
New Approach ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Better Than

A new approach to weapons and equipment effectiveness evaluation based on artificial neural network (ANN) performs better than traditional method, which is in view of the complex relationship between the effectiveness and many factors that influence the evaluation. The structure and learning algorithm of BP neural network is evaluated the fighters’ air-to-air combat capability. The evaluation is accomplished by a two-layer BP neural network and MATLAB toolbox. The simulation results show that the artificial neural network have better generalization ability and approximation performance for continuous function, which is valuable in weapons and equipment effectiveness evaluation application.

Artificial Neural Network for Medical Diagnosis

2014 ◽  
pp. 85-94 ◽  
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Artificial Neural Network ◽  
Drug Development ◽  
Medical Diagnosis ◽  
Artificial Neural ◽  
Intelligent Tools ◽  
Artificial Neural Network Ann

This chapter mentions AI which has various applications in medical diagnosis. One of the most impressive processing tools in this area is the Artificial Neural Network (ANN) that has improved the performance of the existing diagnosis systems. ANN as one of the advanced intelligent tools for medical diagnosis is a subject of researching for finding the algorithms for better medical diagnosis. Applications of ANN in pattern recognition, drug development and medical diagnosis such as hepatitis, cancer and heart diagnosis is wildly investigated by researchers. In this chapter, a brief explanation of ANN for diagnosis of same diseases is provided.

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