SST/Collaborative Research: Self-Supporting Wireless Sensor Networks for In-Process and In-Service Integrity Monitoring Using High Energy-Harvesting Nonlinear Modeling Principles

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The research objectives of this Sensor Small Team (SST)/Collaborative Research grant focus on the derivation of scientific principles for harnessing information from a large network of self-sustainable sensors for quality and integrity monitoring in engineering systems, especially those at the core of manufacturing and service enterprises. The objectives include: fabrication and adaptation of sensors that integrate the piezoelectric micro-power generator components that can harvest energy from the host-environment with components for transmitting the measured signals as radio frequency waveforms and sensor components tuned to measure vibrations and acoustic emission from a host structure; derivation of an approach based on augmenting the current monitoring foundations of statistics and machine learning with nonlinear dynamic principles to decipher information buried in the, conceivably feeble, signals from a network of self-sustainable sensors for monitoring in-service integrity of large complex systems; and validation of the new framework for in-service integrity monitoring of pipeline infrastructure through lab experiments and limited field tests.If successful, this research will create a new pathway to monitor and control large-scale complex civil, biomedical, electro-mechanical, transportation, telecommunications, and environmental systems. It will help in surmounting two major technological barriers in sensing large scale complex systems by obviating the need for wiring, energizing and local processing, and allowing for discerning the complicated patterns, including the nonlinear dynamics, underlying the signals from real-world sensor networks. The research will lead to a novel interdisciplinary graduate program minor in Miniature Wireless Sensing Networks, to be offered jointly by the four participating institutions.