CSR: Medium: Self-organizing Cyber Substrates: Exploring a Modular Computing and Communications Architecture for Structural Health Monitoring

许多物理结构，包括飞机机翼、桥梁、风力涡轮机叶片、水坝和建筑物，都会随着时间的推移而发生裂缝。及早发现这些问题对于防止重大灾难至关重要。一种很有前途的方法是安装传感器，持续监测和报告结构的完整性。然而，由于当前技术的一些限制，包括电池供电传感器需要频繁更换电池，无源传感器的探测范围有限，以及通常涉及射频传感器网络的单独通信子系统，因此采用受到限制。该项目旨在通过探索一系列新技术来消除这些障碍，包括利用结构本身的基板进行机械能收集和超声波通信。这项研究的长期愿景是开发一种变革性的自组织嵌入式系统设计范式，促进自供电计算、自供电网络和结构健康监测融合到“网络基板”中，可以“感知”、“感觉”和“诊断”即将发生的灾难性故障。该方法基于一种新的集成传感、信号处理和通信芯片组，它可以从附着或嵌入的基板上清除应变和振动能量。能量在电容器中积累，用于计算和通信。这些芯片有足够的本地信号处理能力来检测指示故障的事件，因此它们的通信需求减少到每个事件向日志设备发送一个比特。该项目的关键创新在以下领域：1)用于传感、事件分类和超低功耗信号处理的嵌入式计算硬件；2)用于极端能源经济的无包和穿过衬底的脉冲网络；3)从衬底结构中清除能量；4)用于结构健康评估和事件预测的二进制计算模型；5)用于上述所有元素自组织集成的智能嵌入式软件。所有这些组件都是围绕二进制信息框架的核心主题设计的，二进制信息框架在结构处理的传感，通信和全局推理算法中大量利用功率优化。教育和推广活动包括让不同的研究生、本科生和高中生参与研究，以及开发一门新的结构健康监测跨学科研究生课程。

Many physical structures, including airplane wings, bridges, wind turbine blades, dams, and buildings, are subject to the development of fractures over time. Detecting these problems early is essential to preventing major catastrophes. A promising approach is to install sensors that continuously monitor and report on the structure's integrity. However, adoption has been limited because of several limitations in current technology, including a need for frequent battery replacement for battery-powered sensors, limited interrogation range of passive sensors, and a separate communication subsystem usually involving radio frequency sensor networks. This project aims to remove these barriers by exploring a set of new technologies, including mechanical energy harvesting and ultra-sound communication using the substrate of the structure itself.The long term vision of this research is to develop a transformative self-organizing embedded system design paradigm that facilitates convergence of self-powered computing, self-powered networking and structural health monitoring into "cyber-substrates", that can "sense", "feel" and "diagnose" impending catastrophic failures. The approach is based on a new integrated sensing, signal processing, and communication chipset, which scavenges both strain and vibration energy from the substrate to which it is attached or embedded into. Energy is accumulated in a capacitor for computing and communications. These chips are capable of enough local signal processing to detect events indicative of failures, so that their communication requirement is reduced to sending a single bit per event to a logging device. Key innovations in this project are in the areas of: 1) embedded computing hardware for sensing, event classification, and signal processing with ultra-low power budgets, 2) packet-less and through-substrate pulse networking for extreme energy economy, 3) energy scavenging from the substrate structure, 4) binary computation models for structural health evaluation and event predictions, and 5) smart embedded software for self-organizing integration of all the above elements. All these components are designed around the core theme of binary information framework which is heavily leveraged for power optimization in sensing, communication, and global inference algorithms for structural processing. Education and outreach activities include involvement of diverse graduate, undergraduate and high school students in the research, and development of a new interdisciplinary graduate course in structural health monitoring.