Merging experimental design and structural identification around the concept of modified Constitutive Relation Error in low-frequency dynamics for enhanced structural monitoring

The modified Constitutive Relation Error (mCRE) is a model updating functional in which structural parameters are sought alongside mechanical fields as the best trade-off between all available information given by measured data and physics knowledge, without any further assumptions. Its robustness to measurement noise and remarkable convexity properties make it a credible alternative to classical model updating methods. However, the model updating process is still conditioned by the number and location of sensing devices, which makes damage detection in SHM applications a challenging task as the available measurements are usually spatially sparse. The question of optimal sensor placement (OSP) has been largely addressed in the last decades with various strategies that aim at optimizing sensors locations either for modal analysis or structural identification. In this paper, we propose an alternative to these techniques with a new sensor placement strategy dedicated to mCRE-based model updating. It uses the concept of Information Entropy by formulating a modified Fisher information matrix, using the strong connection between mCRE and Bayesian inference. A proof of concept involving an earthquake engineering inspired academic case study, where accelerometers are positioned on a two-story frame structure subjected to random ground motion, permits to illustrate the soundness and efficiency of the proposed methodology compared to other classical OSP techniques. The influence of critical mCRE parameters is shown, as well as the benefits of taking multiple scenarios into account so as to get an OSP that is relevant for a wider range of possible damage occurrences.