Subsecond Model Updating for High-Rate Structural Health Monitoring

Abstract

High-rate monitoring, condition assessment, and control of structural systems experiencing high-rate dynamics is challenging due to these structures experiencing events of timescales below 10 ms. Examples of structures that require high-rate structural health monitoring include spacecraft, hypersonic vehicles, ballistic packages, and active barriers for blast mitigation. Subsecond model updating techniques for this unique class of structures must be capable of tracking the system through rapidly changing input forces and time-varying structural parameters. Moreover, any methodology designed for high-rate structural health monitoring must account for the challenges associated with high-speed data measurement and model updating in its formulation. This work presents and experimentally validates a subsecond model updating methodology for enabling high-rate structural health monitoring of a structure that undergoes system-level changes (i.e., damage) while accounting for uncertainties in the measurements, model, and system. To achieve this, a parallelized residual minimization model updating technique is implemented on an FPGA where model parameters are drawn from a continuously updated parameter pool. The parameter pool is updated based on previous system states and known upcoming events (e.g., impacts). In this work, the DROPBEAR experimental test bed at the Air Force Research Laboratory is used to validate the proposed methodology for a one-degree-of-freedom system with a continuously changing boundary condition. Results demonstrate that a continuously changing boundary condition can be successfully tracked at time intervals of 10 ms or less. Computational speed, prediction accuracy as a function of model size, and the role of measurement noise are examined in this work.