• Title/Summary/Keyword: Vision Based Monitoring

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Recent Advances in Structural Health Monitoring

  • Feng, Maria Q.
    • Journal of the Korean Society for Nondestructive Testing
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    • v.27 no.6
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    • pp.483-500
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    • 2007
  • Emerging sensor-based structural health monitoring (SHM) technology can play an important role in inspecting and securing the safety of aging civil infrastructure, a worldwide problem. However, implementation of SHM in civil infrastructure faces a significant challenge due to the lack of suitable sensors and reliable methods for interpreting sensor data. This paper reviews recent efforts and advances made in addressing this challenge, with example sensor hardware and software developed in the author's research center. It is proposed to integrate real-time continuous monitoring using on structure sensors for global structural integrity evaluation with targeted NDE inspection for local damage assessment.

Development of Vision System Model for Manipulator's Assemble task (매니퓰레이터의 조립작업을 위한 비젼시스템 모델 개발)

  • 장완식
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.6 no.2
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    • pp.10-18
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    • 1997
  • This paper presents the development of real-time estimation and control details for a computer vision-based robot control method. This is accomplished using a sequential estimation scheme that permits placement of these points in each of the two-dimensional image planes of monitoring cameras. Estimation model is developed based on a model that generalizes know 4-axis Scorbot manipulator kinematics to accommodate unknown relative camera position and orientation, etc. This model uses six uncertainty-of-view parameters estimated by the iteration method. The method is tested experimentally in two ways : First the validity of estimation model is tested by using the self-built test model. Second, the practicality of the presented control method is verified in performing 4-axis manipulator's assembly task. These results show that control scheme used is precise and robust. This feature can open the door to a range of application of multi-axis robot such as deburring and welding.

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Computer Vision-based Method to Detect Fire Using Color Variation in Temporal Domain

  • Hwang, Ung;Jeong, Jechang;Kim, Jiyeon;Cho, JunSang;Kim, SungHwan
    • Quantitative Bio-Science
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    • v.37 no.2
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    • pp.81-89
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    • 2018
  • It is commonplace that high false detection rates interfere with immediate vision-based fire monitoring system. To circumvent this challenge, we propose a fire detection algorithm that can accommodate color variations of RGB in temporal domain, aiming at reducing false detection rates. Despite interrupting images (e.g., background noise and sudden intervention), the proposed method is proved robust in capturing distinguishable features of fire in temporal domain. In numerical studies, we carried out extensive real data experiments related to fire detection using 24 video sequences, implicating that the propose algorithm is found outstanding as an effective decision rule for fire detection (e.g., false detection rate <10%).

A Study on the Point Placement Task of Robot System Based on the Vision System (비젼시스템을 이용한 로봇시스템의 점배치실험에 관한 연구)

  • Jang, Wan-Shik;You, Chang-gyou
    • Journal of the Korean Society for Precision Engineering
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    • v.13 no.8
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    • pp.175-183
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    • 1996
  • This paper presents three-dimensional robot task using the vision control method. A minimum of two cameras is required to place points on end dffectors of n degree-of-freedom manipulators relative to other bodies. This is accomplished using a sequential estimation scheme that permits placement of these points in each of the two-dimensional image planes of monitoring cameras. Estimation model is developed based on a model that generalizes known three-axis manipulator kinematics to accommodate unknown relative camera position and orientation, etc. This model uses six uncertainty-of-view parameters estimated by the iteration method.

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A Basic Study on the Instance Segmentation with Surveillance Cameras at Construction Sties using Deep Learning based Computer Vision (건설 현장 CCTV 영상에서 딥러닝을 이용한 사물 인식 기초 연구)

  • Kang, Kyung-Su;Cho, Young-Woon;Ryu, Han-Guk
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2020.11a
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    • pp.55-56
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    • 2020
  • The construction industry has the highest occupational fatality and injury rates related to accidents of any industry. Accordingly, safety managers closely monitor to prevent accidents in real-time by installing surveillance cameras at construction sites. However, due to human cognitive ability limitations, it is impossible to monitor many videos simultaneously, and the fatigue of the person monitoring surveillance cameras is also very high. Thus, to help safety managers monitor work and reduce the occupational accident rate, a study on object recognition in construction sites was conducted through surveillance cameras. In this study, we applied to the instance segmentation to identify the classification and location of objects and extract the size and shape of objects in construction sites. This research considers ways in which deep learning-based computer vision technology can be applied to safety management on a construction site.

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Six-degree-of-freedom Manipulator Displacement Measurement using Stereo Vision (스테레오비전을 이용한 6자유도 머니퓰레이터 변위 측정)

  • Lee, Dong-Hyeok;Baek, So Young;Cho, Nahm Gyoo
    • Journal of the Korean Society for Precision Engineering
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    • v.32 no.2
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    • pp.191-198
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    • 2015
  • In this paper, six-degree-of-freedom (DoF). Displacement measurement technique using a compact stereo-vision system is proposed. The measuring system consists of a camera, an optical prism, two plane mirrors, and a planar marker on a target. The target was attached on an object so that its six-DoF displacement can be calculated using a proposed coordinates estimating algorithm and stereo images of the marker. A prototype was designed and fabricated for performance test. From the test results, it can be confirmed that the proposed measuring technique can be applied to monitoring and control of various manipulators.

Recent R&D activities on structural health monitoring in Korea

  • Kim, Jeong-Tae;Sim, Sung-Han;Cho, Soojin;Yun, Chung-Bang;Min, Jiyoung
    • Structural Monitoring and Maintenance
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    • v.3 no.1
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    • pp.91-114
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    • 2016
  • In this paper, recent research trends and activities on structural health monitoring (SHM) of civil infrastructure in Korea are reviewed. Recently, there has been increasing need for adopting smart sensing technologies to SHM, so this review focuses on smart sensing, monitoring, and assessment for civil infrastructure. Firstly, the research activities on smart sensor technology is reviewed including optical fiber sensors, piezoelectric sensors, wireless smart sensors, and vision-based sensing system. Then, a brief overview is given to the recent advances in smart monitoring and assessment techniques such as vibration-based global monitoring techniques, local monitoring with piezoelectric materials, decentralized monitoring techniques for wireless sensors, wireless power supply and energy harvest. Finally, recent joint SHM activities on several test beds in Korea are discussed to share the up-to-date information and to promote the smart sensors and monitoring technologies for applications to civil infrastructure. It includes a Korea-US joint research on test bridges of the Korea Expressway Corporation (KEC), a Korea-US-Japan joint research on Jindo cable-stayed bridge, and a comparative study for cable tension measurement techniques on Hwamyung cable-stayed bridge, and a campaign test for displacement measurement techniques on Sorok suspension bridge.

An Optoelectronical Flank Wear Monitoring Technique of Cutting Tools (절삭공구 플랭크 마모의 광전자학적 측정 시스템 개발)

  • Jeon, Jong-Up;Kim, Seung-Woo
    • Journal of the Korean Society for Precision Engineering
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    • v.4 no.3
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    • pp.60-68
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    • 1987
  • An optoelectronical method for in process monitoring of flank wear of cutting tools is presented. The method is based upon real-time vision technology in which the tool is illuminated by a beam of laser and then the image of wear zone is taken by a vidicon camera. The image is converted to a series of digital pixel data and processed through an algorithm specially developed for measurement of the wear land width. Detailed aspects of the prototype measurement system byilt for experiment are described, and test results are discussed. As conclusions, it is proved that the methods are effec- tive especially for-in situ application with a measuring accuracy of 0.01mm.

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Development of A Lane Departure Monitoring and Control System

  • Huh Kunsoo;Hong Daegun;Stein Jeffrey L.
    • Journal of Mechanical Science and Technology
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    • v.19 no.11
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    • pp.1998-2006
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    • 2005
  • The lane departure avoidance systems have been considered promising to assist human drivers in AVCS (Advanced Vehicle Control System). In this paper, a lane departure monitoring and control system is developed and evaluated in the hardware-in-the-loop simulations. This system consists of lane sensing, lane departure monitoring and active steering control subsystems. The road image is obtained based on a vision sensor and the lane parameters are estimated using image processing and Kalman Filter technique. The active steering controller for avoiding the lane departure is designed based on the lane departure metric. The proposed lane departure avoidance system is realized in a steering HILS (hardware-in-the-loop simulation) tool and its performance is evaluated with a driver in the loop.

On low cost model-based monitoring of industrial robotic arms using standard machine vision

  • Karagiannidisa, Aris;Vosniakos, George C.
    • Advances in robotics research
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    • v.1 no.1
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    • pp.81-99
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    • 2014
  • This paper contributes towards the development of a computer vision system for telemonitoring of industrial articulated robotic arms. The system aims to provide precision real time measurements of the joint angles by employing low cost cameras and visual markers on the body of the robot. To achieve this, a mathematical model that connects image features and joint angles was developed covering rotation of a single joint whose axis is parallel to the visual projection plane. The feature that is examined during image processing is the varying area of given circular target placed on the body of the robot, as registered by the camera during rotation of the arm. In order to distinguish between rotation directions four targets were used placed every $90^{\circ}$ and observed by two cameras at suitable angular distances. The results were deemed acceptable considering camera cost and lighting conditions of the workspace. A computational error analysis explored how deviations from the ideal camera positions affect the measurements and led to appropriate correction. The method is deemed to be extensible to multiple joint motion of a known kinematic chain.