Damage diagnosis of high-rise buildings under variable ambient conditions using subdomain approach

Tall structures, during their service lifetime, face many scenarios and are often prone to damages. Generally, static or dynamic measurements from the entire structure used while formulating Structural Health Monitoring (SHM) techniques for damage diagnosis. In this paper, an output-only diagnostic technique using decentralized concept (subdomain-based) high-rise buildings, employing Vector form of Autoregressive with exogenous input (VARX) model is developed. version ARX preferred, as vector models more effective in detecting/localising damage, when compared scalar models, due capability predict signals a group sensors per trial. work, equation motion associated building recast into VARX model, aiding decentralised algorithm. New indices have been proposed handle inevitable confounding factors like environmental operational variabilities (EoV), apart measurement noise, avoid false-positive alarms. The effectiveness subdomain based its robustness environmental/operational illustrated synthetic time-history responses 25-storey framed ten-storey experimental steel structure.