A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications

TL;DR: This review paper is intended to summarize the collective experience that the research community has gained from the recent development and validation of the vision-based sensors for structural dynamic response measurement and SHM.

TL;DR: A general overview of the concepts, approaches, and real-life practice of computer vision–structural health monitoring along with some relevant literature that is rapidly accumulating is presented.

TL;DR: An outlook on the future of monitoring systems in assessing civil infrastructure integrity is offered and a detailed analysis of the ML pipelines is provided, and the in-demand methods and algorithms are summarized in augmentative tables and figures.

TL;DR: A comprehensive review of state-of-the-art damage detection techniques for WTBs, including most of those updated methods based on strain measurement, acoustic emission, ultrasound, vibration, thermography and machine vision are provided.

TL;DR: In this paper, the strain measurement error in digital image correlation induced by self-heating of digital CCD and CMOS cameras was extensively studied, and an experimental and data analysis procedure has been proposed and two parameters have been suggested to examine and evaluate this.

TL;DR: In this paper, phase interference of microwave images has been experimented for remote submillimeter-accuracy detection of structural displacements of a real-scale building, subject to tensional stress.

Abstract: For structural health monitoring (SHM) of civil infrastructures, displacement is a good descriptor of the structural behavior under all the potential disturbances. However, it is not easy to measure displacement of civil infrastructures, since the conventional sensors need a reference point, and inaccessibility to the reference point is sometimes caused by the geographic conditions, such as a highway or river under a bridge, which makes installation of measuring devices time-consuming and costly, if not impossible. To resolve this issue, a visionbased real-time displacement measurement system using digital image processing techniques is developed. The effectiveness of the proposed system was verified by comparing the load carrying capacities of a steel-plate girder bridge obtained from the conventional sensor and the present system. Further, to simultaneously measure multiple points, a synchronized vision-based system is developed using master/slave system with wireless data communication. For the purpose of verification, the measured displacement by a synchronized vision-based system was compared with the data measured by conventional contact-type sensors, linear variable differential transformers (LVDT) from a laboratory test.

TL;DR: In this paper, the authors used a high-speed digital video camera to obtain displacement time series at sub-pixel resolution, and the mode shapes were obtained from the time series to find the mode shape difference functions between the damaged and the reference states.