Visual-inertial displacement sensing using data fusion of vision-based displacement with acceleration

Park, Jong Woong; Moon, Do Soo; Yoon, Hyeun Joong; Gómez, Fernando; Spencer, Billie F.; Kim, Jong Ryeol

doi:10.1002/stc.2122

Cited by 62 publications

(40 citation statements)

References 26 publications

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“…Computer vision techniques have grown rapidly in the recent decade and have been applied to various areas of structural health monitoring of civil infrastructures, such as static/vibrational displacement measurement, surface displacement/strain estimation, cable tensile force evaluation, vision‐based structural analysis, 3D rocking motion, and landslide monitoring . Numerous computer vision techniques have been developed including the digital image correlation, phase‐based method, orientation code matching, scale‐invariant feature transform, Harris corner detection, InnoVision, edge‐enhanced matching, and others …”

Section: Introductionmentioning

confidence: 99%

A comprehensive alleviation technique for optical‐turbulence‐induced errors in vision‐based displacement measurement

Luo

Feng

2019

Struct Control Health Monit

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Computer vision-based displacement measurement techniques can be affected by the optical turbulence in the field in hot weather. The optical turbulence can be observed naturally when viewing a thick layer of heated air. The nonuniform density distribution of the air due to heat creates spatial variations in refraction indexes, resulting in distortions in video images and measurement errors in displacements obtained from distorted videos. The effect of optical turbulence on vision-based displacement sensing is first illustrated in the field test conducted in hot weather. Then, the statistical characteristics of the optical-turbulence-induced measurement errors are analyzed and confirmed.And a comprehensive optical-turbulence error alleviation technique, which has two steps, is designed based on the statistical studies. A previously developed high-performance multitarget vision-based displacement measurement technique is utilized in the first step to track multiple targets. Distortions of multiple targets are estimated simultaneously continuously. Targets with the least distortions in each frame are identified and their displacements are extracted as the primary displacement. To further alleviate errors in the primary displacement, an adaptive optical-turbulence error filter is formulated in the second step based on the statistical characteristics of the optical-turbulence errors. Validations of the optical-turbulence error alleviation technique are performed in both laboratory and field tests. Field tests are conducted on the Williamsburg Bridge in the natural environment. After alleviating opticalturbulence and camera vibration errors, frequency domain analyses are conducted on vibrational displacements of the Williamsburg Bridge in response to train passing. K E Y W O R D Scomputer vision, displacement measurement, frequency domain analysis, laboratory and field validation, optical-turbulence error alleviation

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Section: Introductionmentioning

confidence: 99%

A comprehensive alleviation technique for optical‐turbulence‐induced errors in vision‐based displacement measurement

Luo

Feng

2019

Struct Control Health Monit

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“…Compared with similar work mixing vision-based systems with accelerometers (Chang and Xiao 2010;Park et al 2018), the data fusion method used in this study (Xu et al 2017) is an autonomous implementation without any user supervision or involvement. This mixed system could be implemented for applications where accurate and high-resolution displacement data are required and where the structure can be accessed e.g.…”

Section: Focus Of This Studymentioning

confidence: 99%

“…Previous efforts of integrating displacement and acceleration data could be summarised into two categories: (i) by superimposition of two displacement data series (i.e. displacement measurement and integrated displacement from acceleration measurement) covering complementary frequency bands (Hong et al 2013;Park et al 2018); and (ii) by solving state space models based on kinematic equations using Kalman filter (KF) estimation (Chang and Xiao 2010;Kim et al 2014;Li and Chang 2013;Smyth and Wu 2007;Xu et al 2017).…”

Section: Data Fusion Of Displacement and Acceleration Measurementmentioning

confidence: 99%

Accurate Deformation Monitoring on Bridge Structures Using a Cost-Effective Sensing System Combined with a Camera and Accelerometers: Case Study

Brownjohn

Huseynov

2019

J. Bridge Eng.

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Information on deformation is critical for bridge condition evaluation but accurate characterisation, usually via discrete displacement measurements, remains a challenging task. Vision-based systems are promising tools, possessing advantages of easy installation, low cost and adequate resolution in time and frequency domains. However, vision-based monitoring faces several field challenges and might fail to achieve the required level of working performance in some real-world test conditions e.g. involving low-contrast patterns and mounting instability of optical sensors. To make the best use of the potential of vision-based systems, a mixed sensing system consisting of a consumer-grade camera and an accelerometer is proposed in this study for accurate displacement measurement. The system considers automatic compensation of camera shake and involves autonomous data fusion process for noise reduction. The proposed system is demonstrated through a field monitoring test on a short-span railway bridge and is validated to offer higher accuracy and wider frequency range than using a camera alone. Displacement data by the mixed system are demonstrated to be viable for estimating bridge influence line, indicating the potential for bridge condition assessment.

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“…To improve the dynamic range of displacement measurement of vision system and decrease the signal noise, data fusion with acceleration measurement is proposed . Vision sensors are used not only to measure translational displacements but also to measure 6‐DOF generalized displacements including rotation.…”

Section: Introductionmentioning

confidence: 99%

Six‐degree‐of‐freedom generalized displacements measurement based on binocular vision

Chen

et al. 2019

Struct Control Health Monit

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Due to their large flexibility and small damping ratios, harmful vibrations could happen on cables under some external excitations, as for instance the rain-wind-induced vibration, which comes with a translational and rotationalcoupling. An experimental study of the phenomenon would be quite important in view of an appropriate design. However, the available rotational measurement approaches are not suitable for measuring the rotation of cable, because the installation of such devices alters the structural mechanical properties. Recently, low-cost vision-based structural displacement measurement methods have been widely used due to their flexible deployment and the noncontact measurement feature. But they cannot measure the rotational displacements directly. This paper proposes a rotational generalized displacement measurement method based on a binocular vision assisted by a coded cylinder. The three-dimensional coordinates of the coded points are acquired according to photogrammetry schemes. The cylinder centroid and its direction vector are obtained by a cylindrical fitting. Eventually, the translational and rotational generalized displacements are derived. In the cylinder fitting stage, one optimizes the cylinder model parameters via differential search. Experimental verifications are carried out to demonstrate that the proposed six-degree-offreedom (6-DOF) generalized displacement measurement is feasible.

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Visual-inertial displacement sensing using data fusion of vision-based displacement with acceleration

Cited by 62 publications

References 26 publications

A comprehensive alleviation technique for optical‐turbulence‐induced errors in vision‐based displacement measurement

A comprehensive alleviation technique for optical‐turbulence‐induced errors in vision‐based displacement measurement

Accurate Deformation Monitoring on Bridge Structures Using a Cost-Effective Sensing System Combined with a Camera and Accelerometers: Case Study

Six‐degree‐of‐freedom generalized displacements measurement based on binocular vision

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