Structural Health Monitoring of a Prestressed Concrete Bridge Based on Statistical Pattern Recognition of Continuous Dynamic Measurements over 14 years

Abstract

This work describes a vibration-based structural health monitoring of a prestressed-concrete box girder bridge on the A100 Highway in Berlin by applying statistical pattern recognition technique to a huge amount of data continuously collected by an integrated monitoring system during the period from 2000 to 2013. Firstly, the general condition and potential damage of the bridge is described. Then, the dynamic properties are extracted from 20 velocity sensors. Environmental variability captured by five thermal transducers and traffic intensity approximately estimated by strain measurements are also reported. Nonlinear influences of temperature on natural frequencies are observed. Subsequently, the measurements during the first year are used to build a baseline health index. The multiple linear regression (MLR) method is used to characterize the nonlinear relationship between natural frequencies and temperatures. The Euclidean distance of the residual errors is calculated to build a statistical health index. Finally, the indices extracted from the following years gradually deviate; which may indicate structural deterioration due to loss of prestress in the prestressed tendons.

An Improved Objective Function for Modal-Based Damage Identification Using Substructural Virtual Distortion Method

“…, that is, at the i-th natural frequency the frequency response is dominated by the contribution of the i-th mode. Thus, Equation (3) can be approximated and expressed as Equation (4). It can be seen from Equation (4) that the structural i-th mode shape ϕ i (µ) is approximately proportional to H q (µ, ω i (µ)), where…”

“…Structural damage identification plays an important role in SHM, which provides a reliable theoretical foundation for monitoring, early warning and safety assessment of large-scale structures [1]. In recent years, many effective methods for SHM [2][3][4][5][6][7] and structural damage identification [8][9][10][11][12][13] have been presented. However, it is still difficult to identify the extent of structural damage accurately, and one of the reasons is a limited number of measurement points in large-scale structures.…”

Automated Modal Analysis for Tracking Structural Change during Construction and Operation Phases

“…Though the key algorithm of the OMA technique, such as the subspace stochastic identification (SSI) method [3], can be automated in order to track the evolution of modal parameters and detect structural changes under operational conditions [10,11,12,13], some obstacles still exist for a fully automated modal analysis (AMA) procedure. They are summarized as follows:…”

Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses

“…With recent advances in structure health monitoring [1,2,3,4,5] and damage detection [6,7,8,9,10], new technologies and methods has been proposed and developed. With the development of petrochemical industry and the implementation of the National Petroleum Strategic Reserve Plan in China, more and more tanks will be in construction and service.…”