Modelagem e desenvolvimento de algoritmos para pré-processamento de sinais em sistemas mecânicos cuja integridade estrutural é monitorada pelo método da impedância eletromecânica

• Ano de defesa: 2017
• Autor(a) principal: Borges, Júlio Almeida
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; Brasil; Programa de Pós-graduação em Engenharia Mecânica
• Palavras-chave em Português: ISHM; Pré-processamento; pre-processing; PZT; Assinatura de impedância; Impedance signature; Métodos estatísticos; Statistical methods; Estruturas metálicas; Metallic structures; Engenharia mecânica; Mechanical engineering; Finzi Neto, Roberto Mendes; Universidade federal de uberlândia; Programa de pós-graduação em engenharia mecânica; Graduate program in mechanical engineering; CNPQ::ENGENHARIAS; CNPQ::ENGENHARIAS::ENGENHARIA MECANICA
• Link de acesso: https://repositorio.ufu.br/handle/123456789/21166; http://dx.doi.org/10.14393/ufu.di.2017.83

Structural Integrity Monitoring based on the Electromechanical Impedance technique allows the detection of changes in structures, allowing the identification and repair of damages. The technique relies on obtaining impedance signatures from the monitored structure, at various moments of its operation. Possible damages are identified by the mathematical comparison between the signatures obtained. As a very precise technique, variations in temperature and external effects such as vibrations and electromagnetic fields acting on the monitored structure represent perturbations that tend to generate errors in the monitoring process. To make the diagnostic process more robust, it becomes necessary to decouple the true structural alteration effects from those that are considered external interferences. The present work aims to show a case study using an aluminum aeronautical panel as a test body, in which the influence of factors not predicted in the impedance technique is identified and characterized by means of statistical models. To perform these analyzes, experiments were performed using piezoelectric transducers coupled to said panel. The experiments subjected the panel to temperature variation and to the inclusion of simulated damages. From the impedance signature data obtained, the efficiency of the elaborated statistical models was verified, being possible to separate and identify the influence of the simulated damage and the temperature, as well as to establish a confidence interval in the developed analyzes. With these results, it is possible to indicate that the proposed statistical analysis technique becomes a useful tool for data preprocessing in structural monitoring applications based on the electromechanical impedance method.