14-10-2010, 01:05 PM
Prepared by:
M.CHANDANA
P.HARITHA
[attachment=6027]
Introduction
The fault diagnosis of a power system provides an effective means to get information about system restoration and maintenance of the power system. Artificial intelligence has been successfully implemented on fault diagnosis and system monitoring. Expert systems are used by defining rules, for a fault diagnosis. In the present work particularly a new method of “AI” namely “Artificial Neural Network” is used as diagnosing to power system faults. A study has been made by taking a sample models of power systems. The all possible faults of the system were diagnosed and predicted with the help of “Auto-Configuring Artificial Neural Network” namely “Radial Basis Function Network” and the comprehensive study reveals that the proposed method is more efficient, faster and reliable than any other method used for fault diagnosis of power systems.
M.CHANDANA
P.HARITHA
[attachment=6027]
Introduction
The fault diagnosis of a power system provides an effective means to get information about system restoration and maintenance of the power system. Artificial intelligence has been successfully implemented on fault diagnosis and system monitoring. Expert systems are used by defining rules, for a fault diagnosis. In the present work particularly a new method of “AI” namely “Artificial Neural Network” is used as diagnosing to power system faults. A study has been made by taking a sample models of power systems. The all possible faults of the system were diagnosed and predicted with the help of “Auto-Configuring Artificial Neural Network” namely “Radial Basis Function Network” and the comprehensive study reveals that the proposed method is more efficient, faster and reliable than any other method used for fault diagnosis of power systems.