HIGH-SPEED FAULT-DETECTION AND CLASSIFICATION WITH NEURAL NETS Academic Article

abstract

• This paper introduces a new neural net (NN) approach for automated fault disturbance detection and classification. The NN design and implementation are aimed at high-speed processing which can provide selective real-time detection and classification of faults. The approach is extensively tested using the Electromagnetic Transients Program (EMTP) simulations of two quite complex transmission system configurations. The results indicate that the speed and selectivity of the approach are quite adequate for a number of different transmission and distribution monitoring, control, and protection applications. 1995.

authors

• Kezunovic, Mladen

published proceedings

• ELECTRIC POWER SYSTEMS RESEARCH

author list (cited authors)

• KEZUNOVIC, M., RIKALO, I., & SOBAJIC, D. J.

citation count

• 43

complete list of authors

• KEZUNOVIC, M||RIKALO, I||SOBAJIC, DJ

publication date

• August 1995

publisher

• Elsevier  Publisher

keywords

• Data Processing
• Electromagnetic Transients Program (emtp) Simulations
• Fault Analysis
• Neural Networks

Digital Object Identifier (DOI)

• 10.1016/0378-7796(95)00962-X

start page

• 109

end page

• 116

volume

• 34

issue

• 2

URL

• http%3A%2F%2Fdx.doi.org%2F10.1016%2F0378-7796%2895%2900962-x