No abstract

Completely non‐contact and fast measurements are still the focus of vision‐based monitoring in real‐bridge applications. Overall, a fast deflection measurement method, that traces the natural features of structures instead of artificial targets, was developed in this study. More specifically, due to the tiny scale change between images and the small deformation level of small and medium bridges, a simplified fast‐Hessian detector and a pre‐purification‐based RANdom Sampling Consistency (RANSAC) were proposed and verified by performing experiments under different illuminations. The non‐target deformation measurement method based on an improved algorithm was applied to field testing of an arch bridge with 100 m main girder and showed better processing speed and sub‐pixel accuracy than their originals. The optical results obtained by an industrial camera were consistent with other contact‐type sensors, such as level gauges and inclinometers.

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 impacttesting 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 humaninduced 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

Three-dimensional digital image correlation (3D-DIC) is widely used in various measurement fields. Once a DIC setup is established, different parameters, such as lens focal length, pixel size, stereo angle, and working distance, are easy to know or measure; the range of the matching error is generally 0.01-0.02 pixels. It would be very convenient if the measurement error could be estimated based on the parameters above without performing the entire DIC calculation process. In this study, a numerical simulation was conducted to study the variation of the 3D reconstruction error with the stereo angle in different measurement areas. It was found that the error of the center point was closely related to the error of the full field. Therefore, using simple parameters to describe the 3D reconstruction error of the center point is of great significance for estimating the overall error of a DIC system. The general solution of the 3D reconstruction equation was simplified on the premise that high order terms of pixel coordinates could be omitted. The derived error estimation formulas had a simple form and described the 3D reconstruction error of the center point in three directions. Through a set of static experiments, the 3D reconstruction error of a planar object under different stereo angles (from 10° to 120°) was studied. The matching error was calculated by a 2D-DIC software and inserted into the proposed formulas to obtain the estimated error. The estimated error was compared with the results of a 3D-DIC software, and the effectiveness of the proposed method was verified.

Long‐span bridges are susceptible to vortex‐induced vibration (VIV), which affects the serviceability and safety of bridges when the vibration amplitude is too large and lasts for a long time. Traditional contact‐type sensing technologies (i.e., accelerometers and linear variable differential transformer) are inconvenient and dangerous to be installed on long‐span bridges for monitoring VIV events. To address this limitation, this article focuses on the VIV measurement of a long‐span suspension bridge through noncontact sensing strategies. The contribution of this article lies in (1) noncontact sensing technologies including microwave radar, optical camera and video equipment were employed to measure multiple‐point displacements of the studied bridge under VIV events; (2) dynamic properties of the bridge (i.e., natural frequency, damping ratio, mode shapes) and characteristics of the VIV event (i.e., single‐mode vibration and dominant vibration mode switch) were identified by analyzing monitoring data; (3) an early warning framework for VIV event of long‐span suspension bridges was proposed based on monitored dynamic responses and wind fields; specifically, two indicators, the dominant vibration frequency and the similarity between bridge shape and vibration mode shape, were proposed to identify the VIV event, and then the root mean square (RMS) of measured response was further calculated to determine whether there is a need to trigger the warning system or not. The proposed noncontact VIV measurement strategy has the advantage of rapid measurement of vibration magnitude, rapid identification of dynamic properties of the studied bridge and characteristics of the VIV event, which are helpful for the government and bridge owners to make decisions on vibration mitigation measures and to avoid safety issues.