# Research on Damage Localization of Steel Truss-Concrete Composite Beam Based on Digital Orthoimage
## 1 Introduction
[18] designed a bridge monitoring scheme using an unmanned aircraft with a high-definition gimbal camera to collect images of bridge cables in an intensive batch according to the structural characteristics of the bridge and the distribution form of the cables. The effective information is extracted through image processing, and the health condition of the bridge cables is evaluated comprehensively according to the relevant specifications. [PERSON] et al. [19] designed an automatic bridge crack detection system combined with a real-time integrated image processing method, which can be assembled on an unmanned aircraft for real-time data acquisition and processing and which can effectively detect bridge cracks with higher accuracy and speed compared with other detection methods. All of these methods use classical image processing algorithms for the damage identification of structural cracked areas, and the idea is to directly process the underlying pixels and local regions in the image and then output the target region of interest. These classical treatments have certain limitations, such as the need to manually design filters in advance to detect damage and the need to make assumptions about the crack geometry [20; 21; 22], which leads to a serious dependence of the damage identification results on manually hand-picked parameters. If the understanding of cracks and the establishment of crack models are not in place, the extraction of cracks will be invalid, and damage identification will not be possible. The most important point is that the biggest problem of image processing techniques applied in structural damage identification is that the technique requires a priori knowledge of the cracking position. In other words, the location of the damage cracking on the surface of the structure needs to be known in advance in order to track the development of cracks, meaning that the first key issue of damage identification--the location of the damage--is difficult to discriminate by using existing image processingtechniques. Under the condition that the location of the damage is not known in advance, the existing image processing methods are limited by the monitoring resolution, which makes it difficult to locate the early cracking of the structure. Therefore, the research and application of image processing methods in structural damage identification are currently focused on the algorithmic capability of the images, but there is no research on the correlation between the deep information changes in the images due to structural damage and the structural mechanical behavior. In particular, structural types with many truss rods, such as steel truss-concrete composite beams, are prone to damage and require an efficient monitoring method. Any structure can be considered as a mechanical system consisting of stiffness, mass, and a damping matrix. Once structural damage occurs, the structural parameters are changed, resulting in a change in the response of the system. Therefore, changes in the morphological characteristics of the structure can be considered as a sign of the occurrence of early structural damage. The rapid rise of computer image processing technology in recent years has provided the technical support to solve the defects of incomplete measurement data in the parameter damage identification method. By taking the advantages of parametric damage recognition theory and digital image processing technology, respectively, and correlating digital images with the mechanical behavior of structures, a new method of structural damage recognition based on the holographic morphological monitoring of bridges can be formed through cross research.