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Descripción
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| This paper explores the use of Principal Component Analysis (PCA) based on T2 and Q statistic formulation to detect and distinguish damages in structures. The structure used for this study is a blade of a turbine of an aircraft. This blade is excited using a shaker in one side and seven PZT’s sensors are attached on the surface. A known signal is applied and the responses are analyzed. A PCA model is built using data from the undamaged structure. A mass is attached on the surface in four different positions. Data from the damaged structure tests are projected on the model. The principal components, Q-Residual and T2-Hotelling’s distances are analyzed. Q-residual indicates how well each sample conforms to the PCA model. It is a measure of the difference, or residual between a sample and its projection into the principal components retained in the model. T2-Hotelling’s distance, is a measure of the variation in each sample within the PCA model. | |
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Internacional
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Si |
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Nombre congreso
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Workshop on Structural Health Monitoring |
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Tipo de participación
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960 |
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Lugar del congreso
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Cracow-Poland |
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Revisores
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Si |
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ISBN o ISSN
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978-1-932078-94-7 |
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DOI
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Fecha inicio congreso
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02/07/2008 |
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Fecha fin congreso
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07/07/2008 |
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Desde la página
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1089 |
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Hasta la página
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1097 |
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Título de las actas
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Structural Health Monitoring |