FPGA and Microprocessor-Based Smart Wireless Sensing with Embedded Nonlinear Algorithms for Structural Health Monitoring

该项目将通过直接实施数据处理和解释算法的软件进步以及智能无线传感的硬件进步，通过系统集成开发一种新的结构健康监测技术及其应用。特别是，将开发一种新型的非线性模式分类算法，然后将其嵌入到现场可编程门阵列（FPGA）和基于微处理器的处理器核心中，以实现和优化智能无线传感中记录的非线性和非平稳数据集的板载数据处理功能。该项目研究预计将影响基础设施健康评估和监测，减轻地震灾害和国土安全。该提案通过暑期实习与工业合作伙伴Weidlinger Associates和Xilinx建立了密切的联系。将广泛分发关于基于FPGA的智能无线传感新能力的培训材料。参与机构（俄克拉荷马州大学和圣路易斯华盛顿大学）将共同努力，吸引研究生和本科生，特别是来自代表性不足群体的学生。

This project will develop a new structural health monitoring technique and its application through system integration by direct implementation of the software advances in data processing and interpretation algorithms together with hardware advances in smart wireless sensing. In particular, a novel nonlinear pattern classification algorithm will be developed and then embedded into a Field-Programmable Gate Array (an FPGA) and microprocessor-based processor core to enable and optimize the functionality of on-board data processing of nonlinear and nonstationary data sets recorded in smart wireless sensing. The project research is expected to impact infrastructure health assessment and monitoring, earthquake hazard mitigation and homeland security. The proposal develops close ties with industrial partners Weidlinger Associates and Xilinx through summer internships. Training materials on the new capabilities of FPGA-based smart wireless sensing will be disseminated widely. The participating institutions (University of Oklahoma and Washington University in St. Louis) will work together to engage graduate and undergraduate students, especially those from under-represented groups.