Summary In recognition of the importance of the displacement associated with assessing structural condition, many displacement measurement methods have been proposed to date. With advances in optics and electronics, displacement measurement relying on computer‐vision techniques to convert pixel movement into structural displacement has drawn much attention recently, thanks to its simplicity in installation and relatively inexpensive cost. Despite numerous advantages, 2 major obstacles that prohibit the use of vision‐based method are (a) resolution, which is a function of distance between the camera and the structure, and (b) limited frame rate, which both lower dynamic displacement‐capturing capability. In this paper, to enhance the quality of vision‐based displacement measurement, data fusion with acceleration measurement is proposed to improve the dynamic range of displacements while lowering signal noise. To achieve fusion between vision‐based displacement and acceleration, complementary filters and a time synchronization method between 2 different sources were proposed. The proposed methods were verified through numerical analysis and an experimental test, the results of which showed the validity of proposed data fusion.

A tilt sensor can provide useful information regarding the health of structural systems. Most existing tilt sensors are gravity/acceleration based and can provide accurate measurements of static responses. However, for dynamic tilt, acceleration can dramatically affect the measured responses due to crosstalk. Thus, dynamic tilt measurement is still a challenging problem. One option is to integrate the output of a gyroscope sensor, which measures the angular velocity, to obtain the tilt; however, problems arise because the low-frequency sensitivity of the gyroscope is poor. This paper proposes a new approach to dynamic tilt measurements, fusing together information from a MEMS-based gyroscope and an acceleration-based tilt sensor. The gyroscope provides good estimates of the tilt at higher frequencies, whereas the acceleration measurements are used to estimate the tilt at lower frequencies. The Tikhonov regularization approach is employed to fuse these measurements together and overcome the ill-posed nature of the problem. The solution is carried out in the frequency domain and then implemented in the time domain using FIR filters to ensure stability. The proposed method is validated numerically and experimentally to show that it performs well in estimating both the pseudo-static and dynamic tilt measurements.

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While structural displacements are essential information for structural health monitoring, they are not being widely used in practice due to the inconvenience. Recently, vision-based displacement measurement methods have been introduced, which are more convenient and cost effective. However, visionbased methods have generally not been used primarily for the continuous monitoring of structures, due to spatial constraints on obtaining an appropriate location to secure the field of view. A vision device shows not only the changes of objects in the scene but also the relative changes of view according to changes in the position to which it is mounted. Accordingly, this study proposes a methodology for measuring the structural displacement of a location where a camera is mounted, based on a camera motion-induced relative view change. The method is organized into three steps. First, camera calibration is conducted with background targets to derive the camera parameters and coordinates of the target feature points. Second, by tracking the relative changes in the feature points according to the camera motion, the changed 2D-image coordinates of the points are derived. Third, the displacement is calculated through the relationship between the changed 2D-image coordinates and fixed 3D-world coordinates of the target feature points using the camera parameters.The changes in view according to the camera motion are analyzed with simulation tests, and the applicability of the proposed method is verified through experimental tests. The results show that the proposed method can be used to rationally measure structural displacements.