A Vision on Stretchable Bio-Inspired Networks for Intelligent Structures

Major progress has been made recently in structural health monitoring maturing the technology through quantification, validation and verification to promote implementation and fielding of SHM Systems, which are key activities in this workshop. In addition there is a lot of work seeking to detect damage precursors and to deploy SHM systems over large areas, moving the technology beyond hot-spot monitoring to global state sensing for full structural coverage. A large amount of small sensors of multiple types are necessary in order to accomplish this, enabling increased sensing capabilities while reducing parasitic effects on host structures. Traditional sensors are large and heavy, adding to the weight of a structure and requiring physical accommodation without adding to, and potentially degrading the strength of the overall structure. Increased numbers of sensors must also be deployed to span large areas while maintaining or increasing sensing resolution and quantification capabilities. These sensors are typically assembled, wired, and installed individually, by hand, making mass deployment prohibitively time consuming and expensive. In order to overcome these limitations the Structures and Composites Lab at Stanford University has worked to develop bio-inspired microfabricated stretchable sensor networks. Adopting the concept of C-MOS and MEMS fabrication techniques, new methods are being developed to completely integrate networks of large numbers of various micro-scale sensors, processors, switches and all wiring in a single fabrication process. Then the networks are stretched to span areas orders of magnitude larger than the original fabrication area and deployed onto host structures. The small scale components enables interlaminar installation in laminar composites or adhesive layers of built up structures while simultaneously minimizing parasitic effects on the host structure. Additionally, data processing and interpretation capabilities could be embedded into the network before material integration to make the material truly multifunctional and intelligent once fully deployed. This paper reviews the current accomplishment and future vision for these systems in the pursuit of state sensing and intelligent materials for self diagnostics and health monitoring.