Monitoring the Health of Structural Systems from the Geometry of Sensor Traces
CEE Professor Dionisio Bernal received a $194K NSF grant for “Monitoring the Health of Structural Systems from the Geometry of Sensor Traces“.
Deterioration from the passage of time and from exposure to large loading events can reduce the safety of structural systems. The effectiveness and efficiency of interventions to maintain adequate reliability depend on the available information, and the objective of structural monitoring is to provide it. Attempts to characterize deterioration by tracking resonant frequencies has had limited success due to small sensitivity of the features relative to their irreducible variability. This award supports research on an entirely different paradigm, one where monitoring is carried out – not by inspection of frequencies – but by examination of a geometric object, a hyper-dimensional hologram of sorts, built from measurements obtained in closed-loop operation. Progress from this new paradigm may benefit the US economy by reducing the cost of inspections, by advancing the practice of condition based maintenance, and, ultimately, by reducing the life cycle cost of structural systems.
The research casts the monitoring problem as that of tracking the geometry of an object generated by trajectories that are traversed as the system operates autonomously under nonlinear feedback. In contrast with linear feedback, which infers about changes from eigenvalues, nonlinear feedback attempts to map the reference state to the geometry of an attractor and focuses on how system changes affect the resulting manifold. Theory to guide how to specify the nonlinear control so the system has a stable attractor, with a predictable basin of attraction, is currently lacking. The simulation-guided, theoretical research that is central to this work is intended to contribute in filling this knowledge gap. The research tackles also the question of how to select the state from where the system is “launched” so the demands on the necessary actuation are minimized. Albeit the optimal sensor and actuator placement problems are not explicitly included in the scope of the project, exploratory work in both of these issues is planned.