Abstract
Deflections are commonly measured in the static structural system identification of structures. Comparatively less attention has been paid to the possibility of measuring rotations for structural system identification purposes, despite the many advantages of using inclinometers, such as a high resolution and being reference free. Although some work using rotations can be found in the literature, this paper, for the very first time, proposes a statistical analysis that justifies the theoretical advantage of measuring rotations. The analytical expressions for the target parameters are obtained via static structural system identification using the constrained observability method first. Combined with the inverse distribution theory, the probability density function of the estimations of the target parameters can be obtained. Comparative studies on a simply supported bridge and a frame structure demonstrate the advantage of measuring rotations regarding the unbiasedness and the extent of variation in the estimations. To achieve robust parameter estimations, four strategies to use redundant rotations are proposed and compared. Numerical verifications on a bridge structure and a high-rise building have shown promising results.
Highlights
The expression for parameter θ is obtained under the framework of static structural system identification using the observability method
This article proposes a statistical analysis to illustrate the theoretical advantage of measuring rotations rather than deflections in static structural system identification, which is different from the system identification using dynamic data [50,51,52]
The analytical expressions for the target parameters are derived with structural system identification using the constrained observability method
Summary
Potential catastrophic events due to the failure or malfunction of civil infrastructures (e.g., bridges, high-rise buildings, dams) might claim people’s lives and cause substantial economic losses To avoid this undesirable consequence, it is vital to know the current condition of structures. A basic assumption in structural system identification is that the deterioration or the damage of structures is reflected in the change in structural parameters (such as bending and axial stiffness) These parameters can be estimated by various structural system identification methods using a measured response from structures under external excitations. The modal information of structures can be obtained by analyzing the correlation functions or the spectral density matrices computed from the operating response data Among these methods, the Bayesian methods [8] can obtain the posterior distributions of the target parameters by combining the assumed distributions of the parameters in the priors and the evidence from the measurements. A new formulation of observability equation with the measurement error terms separated was proposed in [26]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
