Oct 3, 2009

Autoconfiguring Artificial Neural Network Applied to Fault Diagnosis in Power System

This seminar is based on AI (Artificial intelligence). 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. You can also Subscribe to FINAL YEAR PROJECT'S by Email for more such projects and seminar.


The early detection of faults (just starting and still developing) can help keep away from machine shutdown, breakdown or even catastrophes concerning human fatalities and material harm. Computational intelligence strategies are being investigated as an extension to the conventional fault prognosis methods. artificial Neural Networks is a effective records modeling device that is able to capture and represent complex enter/output relationships.

Artificial intelligence (AI) techniques, particularly the neural networks, are recently having significant impact on fault diagnosis.

This paper gives a comprehensive introduction for the faults analysis and fault calculations. All possible faults of the power system were diagnosed and predicted with the help of “Auto-Configuring Artificial Neural Network”. Both feed forward and feedback or recurrent architectures have been covered in the description. Here a sample power system is selected to test the neural network model.

This paper offers a complete creation for the faults analysis and fault calculations. All possible faults of the power system have been identified and predicted with the assist of “Auto-Configuring artificial Neural network”. both feed ahead and remarks or recurrent architectures had been blanketed within the description. here a sample electricity gadget is selected to test the neural community model.

Artificial neural network, in the present scenario is novel in its technological field and still we have to witness a large of its development in the upcoming era’s, whose speculations are not required, as it will speak for themselves.

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