On-line monitoring of wind-induced stresses and fatigue damage in instrumented structures

The use of sparse-measured response as a means to monitor stresses and fatigue damage throughout metal structures has been the subject of recent work by researchers in the field of vibration-based structural health monitoring. The basic premise is that by using measured structural response, one can improve upon purely stochastic estimates. The most recent applications found in the literature employ the Kalman filter as an estimator. In this paper, we propose a finite element model-based state estimator that can be implemented as a modified version of the finite element model of the system using corrective forces that are proportional to the measurements. In contrast with the standard Kalman filter, the proposed estimator explicitly accounts for spatial correlation and for the colored nature of the excitation through knowledge of its power spectral density. The approach is used to estimate the number of threshold crossings in the bending moment history of a simulated tall vertical structure subject to turbulent wind. It is shown that the proposed model-based estimator outperforms a standard Kalman filter.