# Bridge Displacements Monitoring Method Based on Pixel Sequence
## 3 Experimental Structure Composition  
The experimental model employed in this investigation is a novel assembled I-beam aluminum-supported bridge, depicted in Figure 4. The bridge configuration, akin to a simply supported beam structure, is illustrated in Figure 5, which also depicts the dimensions and specific construction of the test piece. The main beam consists of two prefabricated aluminum alloy I-beams spliced together. The I-beams are standardized with a height of 200 mm, a width of 50 mm, a flange thickness of 5 mm, and a web thickness of 5 mm. Another aspect of standardization involves the ratio of flange thickness to web thickness. The aluminum alloy I-beams on both sides are welded together with three hollow rectangular steels and are consistent with the main beams in terms of material. They are welded to the beam segments and mid-span of the aluminum alloy beams. The bridge deck is made of organic glass, with a rectangular cross-section measuring 12 mm in height and 500 mm in width. The bridge deck is bonded to the longitudinal beams using acrylic adhesive. The model bridge is hinge-supported at both ends, and its calculated span length is 5.64 m. The completed experimental beam and the restraint conditions are shown in the following figure:  
Figure 4: Experimental bridge. In this experiment, it is essential to investigate the degree of deformation of the main beam structure of the bridge under various loads simulated to represent normal working conditions. The experimental design includes the following key points:  
1. Camera arrangement  
The theoretical framework proposed in this paper relies on non-contact computer vision detection technology for analyzing structural displacement measurements. Hence, the utilization of structural imagery data as initial data is paramount for this purpose. Using different acquisition devices can lead to variations in the collected data. Variations in factors like sampling frequency, focal length, resolution, and other device parameters can influence the accuracy of subsequent measurement analyses. Additionally, the outcomes from the same device can vary due to factors like shooting environments, lighting conditions, shooting distances, and camera angles. 2. Displacement sensor (LVDT) for deflection measurement  
The data acquisition system (DH5902N, DHDAS, Jiangsu Donghua Testing Technology Co., Ltd., Jingjiang, Jiangsu China) is used for data collection. The sensors are positioned at the lower edge of the simply supported beam, with one sensor placed every 1/8 span, totaling seven sensors. 3. Loading method  
To assess the suitability of the algorithm introduced in this paper for deflections under various load conditions, we utilize a manual loading approach for incremental loading. This approach allows for the generation of time-history displacement curves for the supported beam. Through the comparison of time-history displacement curves with data retrieved from displacement sensors, one can ascertain the precision of the acquired displacement values. As illustrated in Figure 6, the entirety of the system's components is seamlessly interconnected to work together, thus finalizing the monitoring system for bridge structure displacement. The front-end camera serves as the primary image acquisition system, transmitting the image signal to the computer for processing. Subsequently, the computer outputs the structure monitoring results, facilitating the evaluation of structural health. Figure 5: Diagram of experimental beam structure. In the laboratory, a model car equipped with weights is used to simulate the state of a bridge under the action of loads during normal operation. The feasibility of the proposed algorithm for structural detection is initially assessed through static load monitoring. Following this, its practical application capability is evaluated under dynamic loads. 1. In the image acquisition system, a Canon 5 DS R camera is utilized, maintaining consistent camera parameters under different load conditions (Figure 7).