## 1 Introduction  
Laminates made of different materials, such as plastic and metal, are referred to as hybrid laminates. The combination of metal sheets with fiber reinforced plastics (FRPs) results in completely new property profiles, which are characterized by low weight combined with high specific rigidity and strength. This enables high degrees of lightweight construction. The insertion of the metal layers significantly improves the damage tolerance of the FRP, making the hybrid laminates predestined for use in the aviation industry. A well-known representative is GLARE (Glass Laminate Aluminum Reinforced Epoxy), a glass fiber reinforced epoxy resin aluminum foil laminate, which is the result of further development of the oldest known hybrid laminate, ARALL (aramid fiber reinforced epoxy resin aluminum foil laminate). The layer structure of GLARE consists of glass fiber prepreg layers combined with aluminum sheets. However, due to the use of the thermoset matrix material, which has a long curing time, and the complex plant technology required, the production costs for these hybrid components increase [1]. The challenge to reduce these costs was met in a joint project at ChemnitzUniversity of Technology, and hybrid laminates with a thermoplastic matrix were developed under the brand names CAPAAL(r) (carbon fiber reinforced polyamide aluminum laminate) and CAPET(r) (carbon fiber reinforced polyetheretherketone titanium laminate) [2]. Another approach to decreasing the weight is the integration of additional functions in structural components. Piezoceramic elements, for example, can be injection-molded with electrically conductive polymers and used, for example, for structural monitoring in fiber reinforced plastics [3]. Similarly, piezoceramic fibers--which are inserted into microcavities produced by forming, and joined by forming technology--enable the monitoring of metal components [4]. However, the efficient and large-scale production of hybrid laminates with large-area integration of sensors for detection and localization of impacts and deformations in hybrid sheet metal structural components is not yet available. The forming of hybrid laminates presents a particular challenge in order to avoid failure of the individual layers due to tearing, delamination, and wrinkling. Successful forming can therefore only be achieved by adequate temperature control [5]. [PERSON] [6] goes on to discuss the effect of the core thickness on the mechanical properties. Furthermore, the failure during deep drawing is described, as is the beginning of crack propagation. Further research on the forming of hybrid laminate can be found in [7]. The laminate is preheated and then formed in a heated tool. The exact description of the material properties at elevated temperature, especially near the melting temperature, is a great challenge for the finite element (FE) simulation. A possible approach is the determination of these characteristic values by a representative volume element [8]. Nondestructive testing of hybrid laminates is also intended to detect defects that have a direct effect on the forming properties [9]. One field of application for hybrid laminates is represented by impact detection. In this field of application, three main algorithm approaches have emerged. The first class includes algorithms detecting impacts by precomputed reference values [10; 11]. These algorithms face the drawback of low adaptability, since each component has to be measured individually. The second class represents signal-theoretical approaches for impact detection relying on direction of arrival estimation. Determination of the direction of arrival is based on cross-correlation [12], which is used for impact detection and localization on aircraft wings [13]. The third class covers localization with machine learning methods. For this purpose, various signal properties are extracted and used as inputs for various machine learning training techniques [14].