OICC Press International Journal of Mathematical Modelling & Computations 2228-6233 13 3 2023 09 28 Presenting a Novel Sensitivity-Damage Feature for Damage Detection Using Time-Series Analysis, Output-Only Ambient Vibration Data 0 0 10.30495/ijm2c.2023.1991902.1279 EN Seyed Arman Hashemi Ph.D. Candidate, Civil Engineering Department, Faculty of Civil & Earth Resources Engineering, Islamic Azad University Central Tehran Branch, Tehran Behnam Adhami Assistant Professor, Civil Engineering Department, Faculty of Civil & Earth Resources Engineering, Islamic Azad University Central Tehran Branch, Tehran, Iran Ali Golsoorat Pahlaviani Assistant Professor, Civil Engineering Department, Faculty of Civil & Earth Resources Engineering, Islamic Azad University Central Tehran Branch, Tehran, Iran. Journal Article 2023 09 28 This paper presents a damage identification method for a benchmark structure model using time series analysis of output-only ambient vibration data. To demonstrate the capability of the proposed method, a 3D finite element model based on a benchmark laboratory model is simulated, and a novel damage-sensitivity feature based on autoregressive time series models with exogenous input (ARX) using the output acceleration responses from the sensors. , is presented under the influence of ambient loads in modeling. In the finite element model, minor local damages near the supports that may occur to a bridge during operation are created to demonstrate the robustness and stability of the proposed damage feature. The results showed that the presented damage feature could effectively identify and locate the minor damages made near the supports (which is presented as a challenge in identification studies) accurately and without errors and provide an indication of the extent of the damage.