Fault identification in distribution lines using intelligent systems and statistical methods

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder. © 2006 IEEE.

Damage detection in a benchmark structure using AR-ARX models and statistical pattern recognition

Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.

Anuario estadístico de América Latina, 1979 = Statistical yearbook for Latin America, 1979

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Anuario estadístico de América Latina y el Caribe, 1985 = Statistical yearbook for Latin America and the Caribbean, 1985

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Anuario estadístico de América Latina y el Caribe, 1986 = Statistical yearbook for Latin America and the Caribbean, 1986

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Anuario estadístico de América Latina y el Caribe, 1987 = Statistical yearbook for Latin America and the Caribbean, 1987

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Anuario estadístico de América Latina, 1973 = Statistical yearbook for Latin America, 1973

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Anuario Estadístico de América Latina y el Caribe 1995 = Statistical Yearbook for Latin America and the Caribbean 1995

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