Development of a method for the efficient and contactless material parameter identification of string instruments using parametric model order reduced finite element models

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The goal of the project is the completely noninvasive identification of the material properties of already existing string instruments. Therefore, an efficient model updating method for the identification of material properties is developed. This method can not only be used for the monitoring of material properties of finished instruments from a production line, but can also be applied on the observation of changing material properties of instruments while ageing. Furthermore, this method renders the identification of antique and valuable instruments’ material properties possible. All approaches will be experimentally validated.An experimental setup to identify the modal parameters of string instruments and a detailed numerical model of a guitar yielding a good approximation of experimental results already exist. The project begins with improving this existing model, which already includes fluid-structure-interaction and orthotropic material properties, until the only coarsely known material properties account for the largest model error. Here, the model of the air inside the guitar body and the bracing of the guitar body will be modelled in more detail. The model is then used in a well-proven finite element model updating scheme to identify the material parameters. This is computationally intensive but promises good results for the unknown material parameters.The main goal of the research project is the development of an efficient model updating procedure for material parameter identification using parametrically model-order reduced models. With parametric model order reduction, the number of degrees of freedom and, thus, the computational effort can be significantly reduced while maintaining the parameter dependence. Hence, a significant reduction of the computing time for model updating can be expected.As an alternative, data-based inverse models for direct material parameter identification from experimentally determined modal parameters are evaluated. A data-based model promises a very fast identification of material parameters directly from experimentally determined modal parameters after a complex one-time learning phase during which a lot of training data has to be generated with the numerical model.In addition to the methodology for the efficient identification of material parameters with numerical models, a completely contactless experimental setup for the identification of the modal parameters of stringed instruments will be developed. So far, established methods of experimental modal analysis with impulse excitation are used for the identification of the modal parameters. However, a completely contactless measurement is highly desirable, especially for the investigation of antique and valuable instruments, and will therefore be developed.