Recent advancements and vision toward stretchable bio-inspired networks for intelligent structures

Significant progress has recently been achieved in structural health monitoring, maturing the technology through quantification, validation, and verification to promote implementation and fielding of SHM. In addition, there is ongoing work seeking to detect damage precursors and to deploy structural health monitoring systems over large areas, moving the technology beyond hot-spot monitoring to global state sensing for full structural coverage. A large number of small sensors of multiple types are necessary in order to accomplish the goals of structural health monitoring, enabling increased sensing capabilities while reducing parasitic effects on host structures. Conventional 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 capabilities. Traditionally, these sensors are 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 techniques of complementary metal-oxide semiconductor and microelectromechanical system fabrication, new methods are being developed to create integrated 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 enable 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 article reviews the current accomplishments and future vision for these systems in the pursuit of state sensing and intelligent materials for self-diagnostics and health monitoring.