Structural safety stands as a pivotal concern that significantly impacts the national economy and livelihoods. Safety issues stemming from performance deterioration can lead to substantial economic losses and societal repercussions. The utilization of safety monitoring technology is crucial in comprehending the operational status of structures and ensuring their safety in service. Nonetheless, the precise tracking and identification of key parameters using monitoring data encounter challenges such as input measurements, modeling inaccuracies, and non-stationary noise, etc. The project team meticulously conducted research to enhance both accuracy and efficiency, concentrating on the refined tracking and identification of characteristic parameters. These research findings have earned recognition from more than ten academicians and numerous esteemed scholars globally. The principal investigator became the first Chinese recipient of the EASD Junior Research Award, while the second investigator was honored with the Guanghua Engineering Science and Technology Prize from Chinese Academy of Engineering.

Fig 1 The probabilistic model and probabilistic distance metric of the transmissibility function under complicated operational conditions

Fig 2 Optimal algorithm for online identification of state and characteristic parameters of structures subject to complicated excitations