## 6 Conclusions  
In this study, the dense full-field deformation of a reduced-scale model for a 24m-span self-anchored suspension bridge under multiple damage conditions was captured with the noncontact remote measurement method in a multi visual field. The spatiotemporal sequence static image data under different work conditions were collected to establish the relationship between spatial and temporal. Furthermore, the dense full-field displacement monitoring data of the girder of the test bridge were obtained, and compared with the finite element calculation results. The measurement results of the dial gauge displacement meter were compared. The main conclusions are as follows:  
1. A fixed point uniaxial automatic cruise acquisition device was designed to collect the static images of the bridge facade under different damage conditions. Then, the spatiotemporal sequences of static images were processed by the edge detection method, the edge pixel virtual marker point, the SIFT algorithm and the optical flow algorithm to obtain a dense full-field displacement of the whole test bridge girder, which can be used as the data base to make the structural health monitoring technology more economical, efficient and direct. Compared with other monitoring  
Figure 19: Comparison of girder alignment obtained by two measure method under condition 6. Figure 20: Deformation trend chart. methods, the girder dense points displacement information provides a data-base for more accurate model updating and damage identification. Meanwhile, the technology proposed in this paper is low-cost and can be used as a long-term regular monitoring method to accumulate massive real structural displacement information and provide big data set for the subsequent study of machine learning for damage identification. The optical flow algorithm, which is widely used in video analysis, was used in the static image data set to track the target and calculate the displacement, overcoming the shortcomings of many manual interventions in the early stage of research group. Meanwhile, the number of monitoring points remains the same (i.e. the displacement of each pixel of the lower edge contour line of the girder). The output data are basically consistent with the finite-element prediction and dial gauge measurement. The global holographic deformation curves of the test bridge exhibit similar trends under different damage conditions, with an error of less than 12%. This means that the proposed method in this paper satisfies the engineering requirement on measurement accuracy. A new method of making a virtual target was used. The coordinates of the required lower edge contour of the girder were extracted and then used it to make the pixels of the initial image of the lower edge of the girder as a virtual target back, and then track and calculate the displacement information of all pixels of the contour through the optical flow algorithm. Although this method needs a certain amount of manual intervention in the early stage, it can locate accurately and obtain more measuring point displacement simultaneously. The information obtained from the combination of several points does not really reflect the structural deformation characteristics of the bridge under different damage conditions, and the abnormal local deformation information caused by the damage will be lost. Thus, the dense full-field displacement information is more sensitive to the structural stiffness change. The characteristics of the linear change of the test bridge under different damage conditions indicate a strong correlation between the damage location and degree and the linear change. The relationship between the three can be established, and the method of amplifying the damage and deformation characteristics and carrying out the quantification requires further study. This work is only the first exploration of the dense full-field displacement monitoring of the whole bridge girder using NRS.