Distributed Sensing Via Inductively Coupled Single-Transistor Chaotic Oscillators: A New Approach and Its Experimental Proof-of-Concept
Distributed Sensing Via Inductively Coupled Single-Transistor Chaotic Oscillators: A New Approach and Its Experimental Proof-of-Concept
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通过电感耦合单晶体管混沌振荡器进行分布式传感：一种新方法及其实验概念验证
DOI：
10.1109/access.2020.2976139
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发表时间：
2020
期刊：
影响因子：
3.9
通讯作者：
and Hiroyuki Ito,
中科院分区：
文献类型：
--
作者：
Ludovico Minati;Korkut Kaan Tokgoz;Mattia Frasca;Yasuharu Koike;Leonardo Ricci;Natsue Yoshimura;Kazuya Masu;and Hiroyuki Ito,
环境、生物医学和结构监测的新兴应用需要测量扩展区域的物理变量。由于单独寻址许多传感器可能会导致不切实际的带宽和功率要求，因此需要分布式传感方法，其中直接在整体级别获得读数。反过来，这通常需要能够彼此交互的传感器节点来实现所需的读出统计。在这里，提出了通过基于混沌同步的非线性模拟方法来应对这一挑战的第一个实际步骤。也就是说，单晶体管振荡器代表了非常低复杂度但高度灵活的实体，经实验发现适合通过互感进行无线耦合，实现一种简单形式的光通量遥测。通过数值模拟和大量实验室实验，展示了多个传感器节点之间以及同一传感器节点与外部激励器之间可能相互作用的丰富内容，包括同步、去同步、中继效应和混沌转换。总之，这些结果揭示了从系综动力学的复杂性中准确估计分布式物理量的平均值的可能性和方法。这种新方法为未来在传感应用中使用简单混沌电路的工作提供了重要的蓝图。
Emerging applications across environmental, biomedical, and structural monitoring require the measurement of physical variables over extended regions. Because addressing many sensors individually can result in impractical bandwidth and power requirements, there is a need for distributed sensing approaches wherein readouts are obtained directly at the ensemble level. In turn, this generally requires sensor nodes capable of interacting with each other to implement the required readout statistic. Here, the first practical steps towards approaching this challenge via a nonlinear analog approach based on chaotic synchronization are presented. Namely, single-transistor oscillators, representing remarkably low-complexity yet highly-flexible entities, are experimentally found to be suitable for wireless coupling via mutual induction, realizing a simple form of telemetry for luminous flux. Via numerical simulations and numerous laboratory experiments, a rich repertoire of possible interactions among multiple sensor nodes and between the same and an external exciter is demonstrated, encompassing synchronization, desynchronization, relay effects, and chaotic transitions. Together, these results reveal the possibility and means of accurately estimating the average of a distributed physical magnitude from the complexity of ensemble dynamics. This new approach contributes an important blueprint for future work using simple chaotic circuits in sensing applications.