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Federal do Rio Grande
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EE - Escola de Engenharia

URI permanente desta comunidadehttps://rihomolog.furg.br/handle/1/512

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1996 - 19982

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Autor: search.filters.author.Piccoli, Humberto CamargoData final: 1999

Resultados da Pesquisa

Agora exibindo 1 - 2 de 2
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    Experimental observation of chaotic motion in a rotor with rubbing
    (1998) Piccoli, Humberto Camargo; Webber, Hans Ingo
    This paper presents an application for chaotic motion identification in a measured signal obtained in an experiment. The method of state space reconstruction with delay co-ordinates with the dynamic evolution described by a map is used. Poincar e diagrams, correlation dimensions and Lyapunov exponents are obtained as tools for deciding about the existence of chaotic behaviour. The method is applied to measurements of the lateral displacement of a vertical rotor experiencing rubbing and in some signals chaos is observed. The work concludes that the possibility of chaotic motion is well determined with the observation of Poincar ́e diagrams and computation of Lyapunov exponents. Correlation dimensions computations, strongly influenced by noise, are not convenient tools for investigation of chaotic behaviour in signals generated by mechanical systems.
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    Análise estatística e espectral de dados meteorológicos de superfície
    (1996) Pinto, Ernesto Luiz Casares; Krusche, Nisia; Piccoli, Humberto Camargo
    This article discusses the spectral analysis of daily meteorological data, extracted from the Meteorological Center of the University of Rio Grande (FURG). The time series corresponds to temperature, atmospheric pressure, humidity and evaporation, measured at Rio Grande city, from January 1990 to August 1995. The spectral approach was made using the professional version of MATLAB Software, mainly the Signal Processing Toolbox. Initially, tests were made for stationarity, periodicity and normality of the time series. Afterwards, the spectral and cross-spectral estimation was computed as well as the autocorrelation, cross-correlation and coherence spectrum of the data analysed. During processing of the time series the Hanning Window, and the low-pass and high-pass Butterworth filters were used. Despite the low frequency data aquisition (one value per day), the spectral analysis shows satisfactory results.