Compressed sensing techniques for detecting damage in structures

One of the principal challenges facing the structural health monitoring community is taking large, heterogeneous sets of data collected from sensors, and extracting information that allows the estimation of the damage condition of a structure. Another important challenge is to collect relevant data from a structure in a manner that is cost-effective, and respects the size, weight, cost, energy consumption and bandwidth limitations placed on the system. In this work, we established the suitability of compressed sensing to address both challenges. A digital version of a compressed sensor is implemented on-board a microcontroller similar to those used in embedded SHM sensor nodes. The sensor node is tested in a surrogate SHM application using acceleration measurements. Currently, the prototype compressed sensor is capable of collecting compressed coefficients from measurements and sending them to an off-board processor for signal reconstruction using ℓ1 norm minimization. A compressed version of the matched filter known as the smashed filter has also been implemented on-board the sensor node, and its suitability for detecting structural damage will be discussed.