## 1 Introduction  
As bridges move towards higher heights, larger spans and more complex structural forms, structural health monitoring (SHM) systems using modal- and vibration-based methods have been widely investigated [1; 2]. SHM, as a control system, monitors the state of a large civil engineering structure by measuring the structural response. Monitoring and assessing the health status of structures throughout their life cycle is essential to reduce maintenance expenses and labor costs and ensure the safe operation of structures [3; 4]. As an important method of SHM, the main purpose of dynamic detection technology is to identify and determine structural dynamic parameters [5]. Through a gradual change in parameters, faults can be predicted in advance and the occurrence of major safety accidents can be prevented. These parameters are mainly obtained using experimental modal analysis technology; that is, structural response data are obtained through sensors and data acquisition equipment, and then modal parameters are obtained through parameter identification. Experimental modal analysis has always been one of the research hotspots in the field of health monitoring. Modal tests of large and complex bridge structures to capture more accurate and complete structural responses from the structure and obtain structural dynamic characteristics for condition assessments and safety warnings have become a hot issue of interest, bridging the academic and engineering communities [6; 7]. The first step of modal testing is to determine the number and location of the measurement points of the bridge structure, that is, to install sensors at key parts of the structure to obtain the dynamic characteristics of the bridge and other structural data. Theoretically, the more sensors deployed, the more accurate the response data available. This is feasible for structures such as small bridges but difficult for large and complex bridges [8]. Considering the engineering environment, cost and risk assessments and other factors, the needs of SHM should be met with the lowest number of sensor measurement points. At this time, the result of the modal test depends heavily on the position and number of sensor measurement points, and the optimal number is determined and configured in the best position so as to enhance the accuracy of information acquisition in the modal test. Therefore, research on the optimal arrangement of sensor measurement points is extremely important and has important engineering value and social significance. Scholars have done extensive research on sensor measurement point optimization. [PERSON] [9] proposed a famous efficient independent method in 1991 for optimizing sensor placement in large spatial structures. [PERSON] et al. [10] used modal strain energy (MSE) and the modal assurance criterion (MAC) as fitness functions to study the optimization problem of spatial structure sensors using an improved genetic algorithm. [PERSON] et al. [11] proposed a novel relaxation sequence algorithm. A truss structure and a rigid-frame arch bridge were used as examples to verify the effectiveness of the new algorithm in optimizing sensor placement. [PERSON] et al. [12] proposed an improved optimal sensor placement method based on the sensitively effective independence method, which further optimized sensor placement by using the sensitivity coefficient reflecting structural damage. These studies have achieved good results in the optimized arrangement of sensor measurement points and have provided some reference for further development in this field. However, they did not carry out actual tests to verify whether the accuracy of the test results obtained based on this distribution method met actual engineering requirements after the optimization arrangement was completed.