## 1 Introduction  
With the rapid development of the national economy, civil engineering structures tend to be large-scale and complex. In long-term service, infrastructure such as bridges, tracks, and overhead contact systems will be damaged due to the aging of materials, corrosion, long-term load action, and the influence of fire, earthquake, and other natural disasters [1, 2, 3]. The damage shortens the service life of the engineering structure and threatens the safety of peoples' lives and property. Finding the location of structural damage in time and evaluating the degree of damage can ensure the safe operation of the structure and reduce the loss of individuals' property [4]. In addition, the evolution law of structural performance deterioration can be mastered, the existing design methods can be improved, and the development of structural engineering can be promoted. Therefore, the research on structural damage identification methods has become a hot topic in civil engineering [5]. The core problem of structural damage identification is to judge the occurrence, location, and degree of damage. Since the 1980s, more and more attention has been paid to the research of structural dynamic damage identification based on environmental vibration [6]. Furthermore, a variety of research methods based on structural vibration response have been developed, such as the modal identification method [7], signal processing method [8],model updating method [9], and intelligent optimization algorithm [10]. The principle behind these methods is that damage will change the structural characteristics, such as stiffness, mass, flexibility, and damping, and then change the dynamic response of the structure [11]. Evaluating structural damage based on structural vibration response has been widely developed in the past two decades. For instance, [PERSON] et al. [12] put forward the core idea and process of bridge frequency indirect identification based on cross-bridge vehicle response for the first time. It has the advantages of solid mobility, high efficiency, and economy. It can be tested continuously and quickly without road closure and stopping operation, so it has been rapidly promoted and developed [13; 14]. With the deepening of the research, [PERSON] et al. [15] proposed a damage identification method using the intrinsic mode function (IMF) corresponding to the speed component response of the passing vehicle. Even in bridge deck irregularity, the distribution of bridge damage is successfully identified. However, if the damage is minor, the bridge deck irregularity may cover up the damage characteristics, making the damage challenging to effectively identify. Subsequently, [PERSON] et al. [16] used a one-dimensional convolution neural network to extract the features of structural acceleration to solve this problem. This method can identify small changes in local structural stiffness and mass and is overwhelmingly sensitive to small changes in local stiffness and mass. One of the crucial problems of structural damage detection based on vibration is constructing and extracting sensitive parameters from structural dynamic responses to identify initial damage [17]. Intelligent algorithms, such as artificial neural network (ANN), cuckoo search (CS), and genetic algorithm (GA), are effectively applied to a wide range of optimization problems [18]. These algorithms are based on global search technology and evolve to find the best solution [19]. Their core idea is to use the vibration response of structures to construct the mapping relationship between characteristic damage parameters and actual damage and achieve the purpose of structural damage identification through reasoning, analysis, and calculation. To this end, an intelligent optimization algorithm has also made significant progress in damage identification. Its development trend is mainly reflected in the combination of various methods and the improvement of algorithms. For instance, [PERSON] et al.