Cables and hangers are critical components of long‐span bridges, tension forces of them are needed to be accurately measured for ensuring the safety of bridges. Traditionally, cable tension forces are measured by attached accelerometers or elastomagnetic (EM) sensors, however, applying these sensors into engineering practice are time‐consuming, labor‐intensive, and highly dangerous. To address these problems, an unmanned aerial vehicle (UAV)‐based noncontact cable force estimation method with computer vision technologies was proposed in this article. Basic concept of the proposed method is to use the UAV‐installed camera for capturing vibration images of cables from a certain distance and cable dynamic properties are extracted by analyzing captured images. It includes two aspects: (a) a line segments detector (LSD) was employed for detecting cable edges from captured video and a line matching algorithm was further proposed for extracting dynamic displacements; (b) the frequency difference of adjacent higher modal frequencies identified from relative displacements of the cable was employed for cable force calculation to avoid the difficulty of extracting fundamental frequency from UAV‐captured video. It should be noted that relative displacement herein refers to the difference between displacements of two points on the same cable. Advantages of the proposed method lie in that the proposed LSD and matching algorithm are more robust than traditional correlation‐based algorithm for calculating dynamic displacements of bridge cables and it does not need to adjust predefined parameters (i.e., subset size in correlation‐based algorithms). In addition, the combination of relative displacement and frequency difference‐based cable force estimation has the capability of enhancing the Fourier spectrum magnitude of bridge cables and reducing the effect of UAV motion on extraction of cable vibration frequencies. The effectiveness and robustness of the proposed method was verified by using an experimental inclined cable and field‐testing data of a long‐span suspension bridge. Results show that calculated cable forces with UAV technology have a good agreement with reference values measured by attached accelerometers and fixed camera, demonstrating correctness and robustness of the proposed method for cable force estimation.

Thermal performance analysis of long-span bridges is important for structural design and safety evaluation; however, its experimental investigation using measured field test data is still insufficient. In this article, 1-year monitoring data of a long-span suspension bridge have been processed to study the thermal effects on structural performance under operating conditions. First, long-term temperature and structural response data, including strain, displacements, and suspender frequency/force, were analyzed statistically for evaluating their correlations. Temperature distribution along the main girder in the longitudinal direction and the temperature gradient in the vertical direction were also analyzed. Statistical analysis results show that the temperature distribution along the girder in the longitudinal direction is nonuniform. The strain change of the lower deck is greater than that of the upper deck in a day. Second, a theoretical study regarding the thermal performance analysis was conducted to calculate structural vertical/longitudinal displacements and thermal-induced internal forces by using measured strains. The estimated displacements are comparable with those measured directly from displacement transducers installed on expansion joints and the global positioning system (GPS) installed on four sections of the girder under normal operating conditions.

The rapid impact testing of bridges contains unique advantages. For example, structural parameters, including frequency response function and structural flexibility matrix can be identified; however, additional impact‐testing instruments are required to excite a bridge, restricting the efficiency of the measurement strategy in terms of experimental cost and time. In this paper, a particle image velocimetry‐based method is proposed for the rapid impact testing and system identification of footbridges under pedestrian excitations. The proposed method has shown promising features: (1) pedestrian load is utilized for the impact excitation of footbridges, which is more convenient than the conventional impact‐testing method with additional excitation devices; (2) the human‐induced impact forces under varying jumping scenarios are calculated from image sequences of human motions acquired by a single camera with its noncontact and target‐less characteristics; and (3) both human‐induced impact forces (inputs) and structural responses (outputs) are employed to identify more modal parameters (i.e., scaling factors, modal mass, and structural flexibility). The robustness of the proposed method was successfully validated by a laboratory test of a simply supported beam and field testing of a cable‐stayed footbridge. The proposed method not only could improve the testing efficiency of footbridges, but also could obtain more modal parameters, which can be further utilized for deflection prediction, damage detection, and long‐term performance evaluation.