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

该项目的目标是对现有弦乐器的材料特性进行完全非侵入性的识别。因此，一个有效的模型修正方法的材料性能的识别。该方法不仅可用于监测生产线上成品器械的材料性能，而且可用于观察器械材料性能在老化过程中的变化。此外，该方法还使鉴定古董和贵重仪器的材料特性成为可能。所有的方法都将通过实验来验证。一个实验装置来识别弦乐器的模态参数和一个详细的吉他数值模型，产生了很好的近似实验结果已经存在。该项目首先改进现有模型，该模型已经包括流体-结构相互作用和正交各向异性材料属性，直到唯一粗略已知的材料属性导致最大的模型误差。在这里，吉他主体内部的空气模型和吉他主体的支撑将被更详细地建模。然后，该模型被用于一个行之有效的有限元模型更新计划，以确定材料参数。这是计算密集型，但承诺良好的结果为未知的材料parameters.The研究项目的主要目标是开发一个有效的模型更新程序的材料参数识别使用参数化模型阶减少模型。通过参数模型降阶，可以显著减少自由度的数量，从而减少计算工作量，同时保持参数依赖性。因此，一个显着减少的计算时间模型updation.As一种替代方案，基于数据的逆模型直接从实验确定的模态参数的材料参数识别进行评估。基于数据的模型承诺在复杂的一次性学习阶段（在此期间必须使用数值模型生成大量训练数据）之后，直接从实验确定的模态参数中非常快速地识别材料参数。除了有效识别材料参数的方法之外使用数值模型，本研究将发展一套完全非接触式的弦乐器模态参数辨识实验装置。到目前为止，已建立的方法，实验模态分析与脉冲激励用于识别的模态参数。然而，完全非接触式测量是非常需要的，特别是对于古董和贵重仪器的研究，因此将被开发。

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.