Department of Applied Science and Technology, Politecnico di Torino, Torino, Italy.
Laboratory for Bioinspired, Bionic, Nano, Meta Materials and Mechanics, University of Trento, Trento, Italy.
Sci Rep. 2022 Nov 9;12(1):19045. doi: 10.1038/s41598-022-22898-3.
Spider webs are finely tuned multifunctional structures, widely studied for their prey capture functionalities such as impact strength and stickiness. However, they are also sophisticated sensing tools that enable the spider to precisely determine the location of impact and capture the prey before it escapes. In this paper, we suggest a new mechanism for this detection process, based on potential modal analysis capabilities of the spider, using its legs as distinct distributed point sensors. To do this, we consider a numerical model of the web structure, including asymmetry in the design, prestress, and geometrical nonlinearity effects. We show how vibration signals deriving from impacts can be decomposed into web eigenmode components, through which the spider can efficiently trace the source location. Based on this numerical analysis, we discuss the role of the web structure, asymmetry, and prestress in the imaging mechanism, confirming the role of the latter in tuning the web response to achieve an efficient prey detection instrument. The results can be relevant for efficient distributed impact sensing applications.
蜘蛛网是一种经过精细调整的多功能结构，由于其具有强大的冲击力和粘性等猎物捕获功能而被广泛研究。然而，蜘蛛网也是一种复杂的传感工具，使蜘蛛能够精确地确定撞击的位置，并在猎物逃脱之前捕获它。在本文中，我们提出了一种基于蜘蛛的潜在模态分析能力的新机制，利用蜘蛛的腿作为独特的分布式点传感器。为此，我们考虑了一种包括设计不对称、预应力和几何非线性效应的蛛网结构的数值模型。我们展示了如何通过蛛网的本征模态分量来分解源于撞击的振动信号，蜘蛛可以通过这种方式有效地追踪到震源位置。基于这种数值分析，我们讨论了蛛网结构、不对称和预应力在成像机制中的作用，证实了后者在调整蛛网响应以实现高效猎物检测仪器方面的作用。这些结果对于高效分布式冲击感应应用可能具有重要意义。
