7 resultados para conditional autoregressive models
em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"
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Pós-graduação em Matematica Aplicada e Computacional - FCT
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Pós-graduação em Matematica Aplicada e Computacional - FCT
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Engenharia Mecânica - FEIS
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Adjusting autoregressive and mixed models to growth data fits discontinuous functions, which makes it difficult to determine critical points. In this study we propose a new approach to determine the critical stability point of cattle growth using a first-order autoregressive model and a mixed model with random asymptote, using the deterministic portion of the models. Three functions were compared: logistic, Gompertz, and Richards. The Richards autoregressive model yielded the best fit, but the critical growth values were adjusted very early, and for this purpose the Gompertz model was more appropriate.
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This paper presents a new approach for damage detection in Structural Health Monitoring (SHM) systems, which is based on the Electromechanical Impedance (EMI) principle and Autoregressive (AR) models. Typical applications of EMI in SHM are based on computing the Frequency Response Function (FRF). In this work the procedure is based on the EMI principle but the results are determined through the coefficients of AR models, which are computed from the time response of PZT transducers bonded to the monitored structure, and acting as actuator and sensors at the same time. The procedure is based on exciting the PZT transducers using a wide band chirp signal and getting its time response. The AR models are obtained in both healthy and damaged conditions and used to compute statistics indexes. Practical tests were carried out in an aluminum plate and the results have demonstrated the effectiveness of the proposed method. © 2012 IEEE.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)