Robust Static Structural System Identification Using Rotations

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.

Role of Sensors in Error Propagation with the Dynamic Constrained Observability Method

The inverse problem of structural system identification is prone to ill-conditioning issues; thus, uniqueness and stability cannot be guaranteed. This issue tends to amplify the error propagation of both the epistemic and aleatory uncertainties, where aleatory uncertainty is related to the accuracy and the quality of sensors. The analysis of uncertainty quantification (UQ) is necessary to assess the effect of uncertainties on the estimated parameters. A literature review is conducted in this paper to check the state of existing approaches for efficient UQ in the parameter identification field. It is identified that the proposed dynamic constrained observability method (COM) can make up for some of the shortcomings of existing methods. After that, the COM is used to analyze a real bridge. The result is compared with the existing method, demonstrating its applicability and correct performance by a reinforced concrete beam. In addition, during the bridge system identification by COM, it is found that the best measurement set in terms of the range will depend on whether the epistemic uncertainty involved or not. It is concluded that, because the epistemic uncertainty will be removed as the knowledge of the structure increases, the optimum sensor placement should be achieved considering not only the accuracy of sensors, but also the unknown structural part.

Structural Health Monitoring of 2D Plane Structures

This paper presents the application of the observability technique for the structural system identification of 2D models. Unlike previous applications of this method, unknown variables appear both in the numerator and the denominator of the stiffness matrix system, making the problem non-linear and impossible to solve. To fill this gap, new changes in variables are proposed to linearize the system of equations. In addition, to illustrate the application of the proposed procedure into the observability method, a detailed mathematical analysis is presented. Finally, to validate the applicability of the method, the mechanical properties of a state-of-the-art plate are numerically determined.

Structural System Identification of Elevated Steel Water Tank Using Ambient Vibration Test and Calibration of Numerical Model

This research aims to investigate the feasibility of using ambient vibration testing for system identification of an elevated water tank. To identify the natural dynamic properties, the experimental study is carried out on an elevated steel water tank located in Tehran. The tank is instrumented with a sensitive velocimeter sensor (microtremor), and the ambient velocity of the tank is recorded for 30[Formula: see text]min in three orthogonal axes. Employing the peak-picking method in the frequency domain, the fundamental frequency of the tank is determined as about 1.9[Formula: see text]Hz. Then, the numerical model of the tank is generated and calibrated based on the obtained data. In the primary modeling, the values of natural frequencies of the tank are in good agreement with the results of the ambient vibration data. This finding is judged to be reasonable considering no clear sign of corrosion in the steel material.