In civil engineering structures, modal changes produced by environmental conditions, especially temperature, can be equivalent to or greater than the ones produced by damage. Therefore, it is necessary to distinguish the variations in structural properties caused by environmental changes from those caused by structural damages. In this paper, we present a review of the technical literature concerning variations in the vibration properties of civil structures under varying temperature conditions and damage identification methods for bridge structures. First, the literature on the effect of temperature on vibration properties is roughly divided into experimental and theoretical studies. According to the classification of theoretical research methods, the progress in research on the probability analysis method, the artificial intelligence method, and the optimization algorithm method in this field is reviewed. Based on the different methods of experimental research employed in this field, the experimental research is reviewed according to qualitative and quantitative analyses. Then, damage identification methods for bridge structures are reviewed, considering data-based and model-based methods. Finally, different research methods are summarized.

Civil structures are affected by some environmental factors, such as traffic, ambient temperature, and noises. The change of structural dynamic characteristics arising from these factors may cover up those coming from structural damage, which makes the evaluation of structural health conditions based on vibration data more difficult. To overcome this difficulty, a novel method based on the support vector machine (SVM) and moth-flame optimization (MFO) is proposed to identify the damage of structures considering temperature variations. First of all, SVM is adopted to determine temperature variations and possible damage locations using the first six natural frequencies, and MFO is exploited to locate and quantify the damage accurately through the objective function constructed with a frequency-based multiple damage location assurance criterion (FMDLAC) and modal strain energy-based index (MSEBI). The combination of MFO and SVM can promote the efficiency of damage identification and accurately analyze environmental effects, which is a creative method with good robustness to solve the issue of damage identification considering environmental factors. To verify the effectiveness of the proposed method, a numerical simply-supported beam example considering temperature variations, as well as random noise, is investigated, and the optimal parameters for the method are acquired. Finally, a practical engineering example, the I-40 Bridge, is adopted to confirm the feasibility of the method further. The results demonstrate that the proposed approach is of a good optimization performance and can identify the damage of large complex structures considering temperature variations, which is of great practical application value.

The bearing of a bridge, as a critical component, is important in the force transformation of the superstructure; however, due to the service condition and repeated impact load, the bearing is prone to be damaged but difficult to detect the damage; the present research has few studies that focused on the damage detection of the structural bearing. Meanwhile, practical engineering is always surrounded by variational environmental conditions, and sometimes, the element and bearing damage both exist in the structure. Thus, these uncertain conditions all cause inaccurate damage identification results using the vibration‐based damage detection method. In order to detect the damage of the structural bearing and improve the precision, firstly, the structural dynamic characteristic equation considering uncertain conditions has been deduced; then, a damage detection framework constructed by the Bayesian theory and perturbation method has been developed in this article; a numerical example of an 8‐span concrete continuous beam and a practical example of I‐40 steel‐concrete composite bridge are utilized to validate the feasibility of the proposed method, and single type and two types of damage cases are studied. The outcomes demonstrate that the damage of structural elements and bearings can be detected with high accuracy. The proposed method is of great applicability and good potential.