Development of a structural identification methodology with uncertainty quantification through the SSI and bootstrap techniques

• Published in: Mechanical systems and signal processing 2022-02, Vol.165, p.108290, Article 108290
• Main Authors: Silva, Edilson, Magluta, Carlos, Roitman, Ney, Filho, Luiz Aragão
• Format: Article
• Language: English
• Subjects: Algorithms; Bootstrap; Damage detection; Mathematical models; Model updating; Random signals; Resampling; Robustness (mathematics); Signal processing; SSI-DATA; Steel beams; Structural health monitoring; System identification; Uncertainty; Uncertainty quantification; Vibration analysis; Vibration tests
• ISSN: 0888-3270; 1096-1216
• DOI: 10.1016/j.ymssp.2021.108290

•Developed method presents an efficient interaction between the SSI-DATA and the bootstrap through RD function blocks.•The proposed framework improved the uncertainty quantification in the estimation of modal parameters through SSI-DATA method.•Numerical and experimental results demonstrate a significant increase in accuracy and precision of the parameter estimates. In the last few years, increasing attention has been given to obtaining reliable results in system identification as a key step in performing model updating, damage detection and structural health monitoring. Many methods have been developed to measure the uncertainty in modal estimates. Some techniques are based on signal resampling to obtain a larger sample space and consequently better process statistics. Thus, this study proposes a new method to quantify uncertainties using the stochastic subspace identification (SSI) technique combined with bootstrap resampling. To validate and compare the performance of the proposed algorithm, two algorithms previously mentioned in the literature were implemented. The first is based on the “moving block method”, and the second is based on blocks of the projection matrix. The proposed method initially generates random decrement functions from signal segments and later uses these functions as bootstrap resampling blocks in SSI. To validate and compare the performance of the proposed algorithm, numerical simulations and two experimental analyses are performed. The first analysis involves a simply supported steel beam subjected to vibration tests through random impacts, and the second involves a three-dimensional four-story frame subjected to vibrations from random signals generated by an electrodynamic exciter. The results of the proposed technique were more robust and accurate than those of the other methods.