Author
Chuan-Zhi Dong
Other affiliations: Zhejiang University
Bio: Chuan-Zhi Dong is an academic researcher from University of Central Florida. The author has contributed to research in topics: Structural health monitoring & Displacement (vector). The author has an hindex of 14, co-authored 37 publications receiving 640 citations. Previous affiliations of Chuan-Zhi Dong include Zhejiang University.
Papers
More filters
••
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.
Abstract: Structural health monitoring at local and global levels using computer vision technologies has gained much attention in the structural health monitoring community in research and practice. Due to t...
248 citations
••
TL;DR: The purpose of this review article is devoted to presenting a summary of the basic theories and practical applications of the machine vision-based technology employed in structural monitoring as well as its systematic error sources and integration with other modern sensing techniques.
Abstract: In the past two decades, a significant number of innovative sensing and monitoring systems based on the machine vision-based technology have been exploited in the field of structural health monitoring (SHM). This technology has some inherent distinctive advantages such as noncontact, nondestructive, long distance, high precision, immunity to electromagnetic interference, and large-range and multiple-target monitoring. A lot of machine vision-based structural dynamic measurement and structural state inspection methods have been proposed. Real-world applications are also carried out to measure the structural physical parameters such as the displacement, strain/stress, rotation, vibration, crack, and spalling. The purpose of this review article is devoted to presenting a summary of the basic theories and practical applications of the machine vision-based technology employed in structural monitoring as well as its systematic error sources and integration with other modern sensing techniques.
144 citations
••
TL;DR: This study proposes a novel structural displacement measurement method using deep learning-based full field optical flow methods that gives higher accuracy than the traditional optical flow algorithm and shows consistent results in compliance with displacement sensor measurements.
Abstract: Current vision-based displacement measurement methods have limitations such as being in need of manual targets and parameter adjustment, and significant user involvement to reach the desired result...
90 citations
••
TL;DR: In this article, a vision-based structural displacement measurement system integrated with a digital image processing approach is developed, which is evaluated by comparing the results simultaneously obtained by the visionbased system and those measured by the magnetostrictive displacement sensor.
85 citations
••
TL;DR: This framework overcomes the issue of single-point monitoring by utilizing an advanced visual tracking algorithm based on optical flow, allowing multi-point displacement measurements and a synchronization mechanism between a multiple-camera setup and a sensor network is built.
Abstract: In this study, a vision-based multi-point structural dynamic monitoring framework is proposed. This framework aims to solve issues in current vision-based structural health monitoring. Limitations ...
76 citations
Cited by
More filters
••
TL;DR: An overview of recent advances in computer vision techniques as they apply to the problem of civil infrastructure condition assessment and some of the key challenges that persist toward the goal of automated vision-based civil infrastructure and monitoring are presented.
500 citations
••
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.
374 citations
••
TL;DR: The state‐of‐the‐art methods have been presented by conducting a detailed literature review of the recent applications of smartphones, UAVs, cameras, and robotic sensors used in acquiring and analyzing the vibration data for structural condition monitoring and maintenance.
301 citations
••
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.
Abstract: Structural health monitoring at local and global levels using computer vision technologies has gained much attention in the structural health monitoring community in research and practice. Due to t...
248 citations
••
TL;DR: Video-processing procedures in this paper are summarised as a three-component framework: camera calibration, target tracking and structural displacement calculation, with discussions about the relative advantages and limitations.
Abstract: Vision-based systems are promising tools for displacement measurement in civil structures, possessing advantages over traditional displacement sensors in instrumentation cost, installation efforts and measurement capacity in terms of frequency range and spatial resolution. Approximately one hundred papers to date have appeared on this subject, investigating topics like system development and improvement, the viability on field applications and the potential for structural condition assessment. The main contribution of this paper is to present a literature review of vision-based displacement measurement, from the perspectives of methodologies and applications. Video-processing procedures in this paper are summarised as a three-component framework: camera calibration, target tracking and structural displacement calculation. Methods for each component are presented in principle, with discussions about the relative advantages and limitations. Applications in the two most active fields, bridge deformation and cable vibration measurement, are examined followed by a summary of field challenges observed in monitoring tests. Important gaps requiring further investigation are presented, e.g. robust tracking methods, non-contact sensing and measurement accuracy evaluation in field conditions.
190 citations