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Influence line (IL) has emerged as very promising damage indices for bridge damage detection. This study proposed a method to localize and quantify damage in beam structures by estimating section flexibility change from deflection IL (DIL) change. To this end, the relationship between second derivative of DIL change and flexibility change was established. To remove noise interference in measurement, piecewise quadratic functions were used to fit and replace noisy DIL change curves, wherein the coefficients of quadratic function were determined via a sparse regularization method, considering the sparsity nature of damage that typically takes place in only a limited number of elements. The feasibility and accuracy of the proposed method are verified through numerical examples and laboratory experiments. Through four hypothetical damage scenarios of a simply supported beam with one or two damaged locations, its ability to quantify minor damage and its anti-noise robustness were well verified. Finally, a laboratory experiment on a simply supported aluminum beam illustrated that the location and extent of damage could be successfully identified in the single-damage and double-damage cases. The numerical and experimental results indicate that the proposed method is promising for future damage localization and quantification of bridge structures. [ABSTRACT FROM AUTHOR]

Summary: Influence lines (ILs) have recently been proposed as an emerging index for structural damage localization. This study investigated a novel damage detection and quantification method that is based on deflection ILs (DILs) for beam structures. By reconstructing DIL matrices using a matrix decomposition method, the relationship between structural damage and changes in DILs was revealed. Subsequently, a DIL‐based method was proposed to locate and quantify damage in beam structures. Numerical case studies and laboratory experiments were conducted to investigate the effectiveness of the proposed method in different scenarios, namely, single or multiple damages in a one‐span simply supported beam and a two‐span continuous beam. Satisfactory damage localization and quantification results were achieved even with noise interference in the measurements. The influences of sensor number and locations were also examined in the numerical studies. In general, an increasing number of sensors and short distance from the measurement points to the damage locations benefited the damage detection accuracy. The numerical and experimental results demonstrated that the proposed DIL‐based method will be a promising field detection technique for the localization and quantification of damage in bridges. [ABSTRACT FROM AUTHOR]

Numerous long-span suspension bridges have been built worldwide over the past few decades. To ensure the safety of such bridges and their users during the bridge service life, several bridges have been equipped with Structural Health Monitoring Systems (SHMSs), which measure dynamic bridge responses and various loading types on-site. Integrating SHMS and damage detection technology for condition assessment of these bridges has become a new development trend. Recent studies have proven that stress influence line (SIL)-based damage indices achieve excellent damage detection performance for a long suspension bridge. However, an accurate and prompt manner of identifying the SIL of a long suspension bridge is important to facilitate the development of the SIL for an effective damage index. Identifying the SIL from field measurement data under in-service conditions has several advantages over the traditional static loading test. This study proposes and develops a new SIL identification method by integrating the least squares solution and Weighted Moving Average (WMA) based on the measured train information and the corresponding train-induced stress time history. The efficacy of the proposed method is validated through its application to Tsing Ma Bridge (TMB). The good agreement between the identified and baseline SILs for a typical diagonal truss member verifies the effectiveness of the proposed method. Furthermore, robustness testing is performed by identifying SIL on the basis of information on different trains and train-induced stress responses and by identifying the SIL of different types of bridge components. Results indicate the feasibility of the application of the proposed approach to SIL identification for long-span bridges. [ABSTRACT FROM AUTHOR]

Numerous long-span cable-supported bridges have been built throughout the world in recent years. These bridges begin to deteriorate once built and continuously accumulate damage during their long service life. The growing popularity of comprehensive structural health monitoring systems (SHMSs) in recently built long-span bridges has started a new trend of integrating SHMS and damage detection technology for real-time condition assessment of these bridges. This paper explores a novel damage detection technique based on stress influence lines (SILs) of bridge components and validates the efficacy of the technique through a case study of the Tsing Ma suspension bridge. A mathematical regularization method is first introduced to identify SILs based on the in situ measurement of train information and train-induced stress responses in local bridge components. Good agreement between the identified and baseline SILs demonstrates the effectiveness of the proposed identification method. Damage indexes based on SILs are subsequently proposed and applied to hypothetical damage scenarios in which one or two critical bridge components are subjected to severe damage. The comparison suggests that the first-order difference of SIL change is an accurate indicator of the damage location. Results of this study indicate that the proposed SIL-based method offers a promising real-time technique for damage localization in long-span cable-supported bridges equipped with comprehensive SHMSs. [ABSTRACT FROM AUTHOR]