Hardware Software Co-Design for Impact Localization using Hybrid Laminates

Stephan Lede, René Schmidt, André Böhle, Wolfram Hardt
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Abstract

Impact detection using piezoelectric sensors is an actual and widespread research field. The current work provides an approach for a real-time realization of an impact detection system using deep learning methods. For realization a hardware software co-design approach is used utilizing hardware acceleration by a continuous pipelining FPGA structure. The concept describes the hardware software partitioning of the underlying functions and the methodology for ensuring continuous data processing and the associated real-time capability. The behavior of the hardware is realized with the help of a finite state machine and thus the correctness of the data is ensured and the impact identification is realized. The results show the real-time capability as well as a reasonable resource utilization of the FPGA design.
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利用混合层压板进行冲击定位的硬件软件协同设计
使用压电传感器进行撞击检测是一个实际而广泛的研究领域。目前的工作提供了一种利用深度学习方法实时实现冲击检测系统的方法。为了实现该系统,我们采用了硬件软件协同设计方法,利用连续流水线 FPGA 结构进行硬件加速。该概念描述了底层功能的硬件软件分区,以及确保连续数据处理和相关实时能力的方法。在有限状态机的帮助下实现了硬件行为,从而确保了数据的正确性并实现了影响识别。结果显示了 FPGA 设计的实时性和合理的资源利用率。
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