Synergistic bridge modal analysis using frequency domain decomposition, observer Kalman filter identification, stochastic subspace identification, system realization using information matrix, and autoregressive exogenous model

This paper presents multiple system identification of large-scale bridge structures proposing the combined usage different modal parameter findings, namely from Frequency Domain Decomposition, Observer Kalman Filter Identification/Eigensystem Realization Algorithm, Combined Deterministic Stochastic Subspace Identification, System Using Information Matrix, and Autoregressive Exogenous Model. A method-centric democratic ranking approach visualizes quantifies harmony among methods in terms parameters, then ranks them based on correlation each other, consequently complies with highest rank outputs. The synergistic scheme is applied a numerical beam two including one healthy another subjected to progressive damage. Looking at top-rank selections, can see that outlier results population parameters intuitively become extinct. collaboration dependent chosen methods; therefore, method selection relies care fair representation features. Lack agreement between indicate low confidence outranking quantified by median absolute deviation. Nevertheless, majority algorithm agrees specific results, which are valuable produce state knowledge despite signal noise ratio, especially without presence reference. Thus, collaborative systematic ranking-based manner reduces significant error possibilities due algorithm-related issues, novel contribution this study.