In this study, the Dempster–Shafer (D–S) evidence theory-based approach for structural damage detection is presented. First, the damage basic probability assignment (BPA) function of substructures using each data set measured from the monitored structure is calculated. Then, the D–S evidence theory is employed to combine the individual damage BPAs in order to reach the final damage detection results. To reduce the computational cost of this method when used in complex structures, the preliminary damage range is first localized by modal strain energy method. An experimental investigation on a 20-bay rigid truss structure is carried out to illustrate the identified ability of the proposed approach with considering the uncertainty of model and measurement noise. The results indicate that the damage detection results obtained by combining the damage BPAs from each test data are better than the individual results obtained by each test data separately.

As the final stage of damage identification, damage severity identification has great significance to structural safety assessment and decision-making in maintenance. Take the damage detection of truss structures for instance; the stochastic damage locating vector method has great advantages. However, the method is a localization technique designed to provide information in damage location only. Many present damage severity identification methods suffer from great error due to high noise. Therefore, it is imperative to develop a new identification method for truss structural health monitoring. To solve this problem, this paper presents the model updating method of damage severity identification based on four cost functions: (i) correlation coefficient of free vibration accelerations; (ii) correlation coefficient of local mode shapes; (iii) free vibration accelerations assurance criterion; and (iv) local modal assurance criterion. In these functions, correlation coefficient and correlation degree of free vibration accelerations of measured nodes are first proposed to identify damage severity. Moreover, a simple supported bailey steel-truss bridge Benchmark Model has been designed and constructed. The span is 8 m with the scaled ratio 1:25. Based on the model, both experimental and numerical simulation results using these procedures under pulse excitation indicate that they are feasible and effective. In addition, the proposed techniques exhibit high-noise insusceptibility. Copyright © 2011 John Wiley & Sons, Ltd.

Accurate structural damage localization in engineering is still a challenge due to high noise and low accuracy of the structural finite element model. With the most basic type of construction, the simply supported beam is the most widely used type of structures in short and medium span bridges. Therefore, it is imperative to study their damage detection methods, which can be used in engineering. To solve this problem, an alternative method for damage detection is proposed in this study on the basis of fractal theory and curvature mode shapes method: the curvature difference probability method of waveform fractal dimension. The influence of different amplitudes of excitation on results and the robustness against noise are also discussed. Based on a simply supported beam model in the laboratory, both the experimental and numerical results using the technique under step or pulse excitation indicate that the proposed method can be used in damage localization very well, and it exhibits high-noise insusceptibility: it is still feasible even if the noise level is up to 15%, which lays a good foundation for engineering application. Moreover, the proposed technology needs no finite element model of the detected structures. Therefore, it is quite simple in the procedure.

This work proposes an efficient and reliable method for damage localization in truss structures. The damage is localized on the basis of measured acceleration signals of the structure followed by simple statistical signal processing. It has three main advantages over many existing methods. First, it can be directly applied to real engineering structures without the need of identifying modal parameters or solving any global optimization problem. Second, the proposed method has higher sensitivity to damage than some other frequently used methods and allows to localize damage as small as a few percentages. Third, it is a model-free method, which does not require precise finite element model development or updating. Validation of the method has been conducted on numerical examples and laboratory-scale trusses. Two types of frequently used trusses have been selected for this study, namely, Howe and Bailey trusses. The presented experimental validation of the method shows its efficiency and robustness for damage localization in truss structures.