Uma contribuição ao método de síntese modal experimetal

• Ano de defesa: 2006
• Autor(a) principal: Junqueira, Manoel Moraes
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; BR; Programa de Pós-graduação em Engenharia Mecânica; Engenharias; UFU
• Palavras-chave em Português: Normalização; Identificação; Síntese modal experimental; Modelagem dinâmica; Vibração; Mecânica dos sólidos; Dinâmica; Normalization; Identification; Experimental modal synthesis; Dynamic modeling; CNPQ::ENGENHARIAS::ENGENHARIA MECANICA
• Link de acesso: https://repositorio.ufu.br/handle/123456789/14782

The determination of the dynamic parameters of great or complex structures can be made using modal synthesis methods subdividing the complete structure in substructures. The employment of this method may be done by using analytical or experimental procedures. Generally speaking, poor eigenvalues and eigenvectors may be identified using experimental modal synthesis methods due to a normalization deficient process of the modal bases and to the low orthogonality condition of the identified bases. The contribution of this current work is about the improvement of the great or complex structures dynamic identification process by using the experimental modal synthesis method. The basis of this research methodology is the SMFR (Modal Synthesis with Residual Flexibilities) method and an identification of the physical matrices of the system by using the experimental FRF (Frequency Response Function), called ACS (Simultaneous Curve Fitting) method. These matrices contribute to the improvement of the orthogonality conditions and normalization of the experimental modal bases. Simultaneously, two new methods (CSME and CSMF) for the automatic choice of the used substructures modal bases in the modal synthesis process have been developed. The validation procedures of these methodologies were developed by using examples of numerical simulation and experimental models. Using CSMF method, it was possible to improve the modal choice process, automatizing and minimizing the interference of the user in the modal synthesis method. In the case of experimental data with high level noise, the recommended is the iterative method.