## 3 Signal Processing  
### System Description  
The sensor function of the hybrid laminate uses the piezoelectric effect. Mechanical loads on the multifunctional lightweight structure, e.g., impacts on the surface, induce displacements of the electrical dipoles within the piezoceramic particles. These displacements generate measurable electrical voltages between the copper electrodes and the aluminum sheet of the hybrid laminate, which can be further processed with the assistance of digital measuring methods. One possible application is represented by impact detection, which is used as an exemplary case for showing the functionality of the manufacturing process of the sensors, as well as the given practical usability. In our previous work, [PERSON] et al. showed that, with the same sensors, a sufficiently high localization accuracy can be achieved on the basis of a Support Vector Machine (SVM) usage combined with time difference computation, although the test objects are mathematically difficult to describe [26]. However, for practical use, real-time functionality has to be ensured, just as energy efficiency must be confirmed. The previous solutions from [26] offer a solid basis for data collection and evaluation, but they are unsuitable for practical use. The main problem is represented by the used UART Interface, since the provided data rates are too small for the large amounts of data, leading to big buffers accompanied  
Figure 6: Formed hybrid laminates with sensor functionality in two versions: (**a**) without electrodes and (**b**) with electrodes at preheating temperature 180 \({}^{\circ}\)C and tool temperature 150 \({}^{\circ}\)C.  
by high hardware requirements. The second main problem is that data processing on conventional PCs limits the practical use in cars or airplanes. For this reason, the process was transferred to an energy-efficient embedded system on chip (SoC) design, providing real-time capability, low power consumption, flexible application possibilities, and the accuracy necessary for real-world scenarios.  
The basis for the design is a Zynq XC7Z010 SoC provided by Xillinx, representing a combination of FPGA and a Cortex A9 ARM processor connected by a standardized AXI interface, providing fast and highly flexible communication methods accompanied by high data throughput. The novel system architecture is depicted in Figure 7. As a test object, a center console with four sensors was used--three were placed in a vertical column and one was off-centered with a base distance of 5 cm. The object is stimulated by a light impact generated by contact from a human finger, leading to a visible voltage difference at the sensors. However, the sensor signals have a very low impedance, leading to insufficient measurement results by ADC usage. For data acquisition, the analog signals have to be stabilized energetically first. Afterwards, the signals must be transformed to the corresponding measuring range of the ADC. This task is performed by an electric circuit, which ensures the correct transformation of the analog signals to digital signals. The stabilized data are sampled and digitized using Xilinx's integrated XADC. The configuration and data sampling are handled by the ADC interface depicted in Figure 7. In the following steps, the data are smoothed by a moving average filter, and the necessary features are extracted and implemented on the FPGA. The resulting features are transferred to the SVM classification process realized in software executed on the ARM processor. Due to embedded Linux usage on the processor part, all arbitrary communication interfaces, like Ethernet, CAN, or UART, can be used to send the localization results to the most common possible applications. In the following, the necessary steps for impact detection are explained in detail.