Detect and classify faults using neural nets Academic Article

abstract

• A neural network trained to recognize patterns of transmission line faults is incorporated in a PC-based system that analyzes data files from substation digital fault recorders (DFRs). Recently, such a package, called DFR Assistant, was developed which can be installed locally in a substation. As soon as the DFR records a disturbance, data is automatically transferred to the PC and the fault analysis software determines if a fault has occurred and, if so, the type of fault. This conclusion is used to check if the relay operation is correct or not.

authors

• Kezunovic, Mladen

published proceedings

• IEEE COMPUTER APPLICATIONS IN POWER

altmetric score

• 3

author list (cited authors)

• Kezunovic, M., & Rikalo, I.

citation count

• 74

complete list of authors

• Kezunovic, M||Rikalo, I

publication date

• October 1996

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE COMPUTER APPLICATIONS IN POWER  Journal

keywords

• 40 Engineering
• 4009 Electronics, Sensors And Digital Hardware
• 46 Information And Computing Sciences

Digital Object Identifier (DOI)

• 10.1109/67.539846

start page

• 42

end page

• 47

volume

• 9

issue

• 4

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2F67.539846