Defect detection in concrete structures using sensor fusion of force sensor and camera

被引:0
|
作者
Louhi Kasahara J.Y.
Minato S.
Moro A.
Woo H.
Yamashita A.
Asama H.
机构
基金
日本学术振兴会;
关键词
Clustering; Computer vision; Defect detection; Force sensor; Sensor fusion;
D O I
10.2493/jjspe.86.975
中图分类号
学科分类号
摘要
Inspection of concrete structures such as tunnels and bridges is most often performed in outdoor environments where wind and vehicle noise are strongly present. Therefore, inspection methods must be robust against acoustic noise. The use of an impact hammer, which has a force sensor embedded in its head, has the advantage of being inherently robust against acoustic noise compared to the commonly used acoustic hammering inspection method while retaining the same ease of use. However, being able to capture data only during the short impact time, force sensor alone does not allow for acceptable defect detection. Therefore, in this study, the detection performance of defects was improved by considering the position of the crack on the concrete surface and the sample position obtained from a camera image in addition to the response of the force sensor of the impact hammer. From the experimental results obtained using concrete test blocks in laboratory conditions, the ability to detect defects with an impact hammer was significantly improved. © 2020 Japan Society for Precision Engineering. All rights reserved.
引用
收藏
页码:975 / 981
页数:6
相关论文
共 50 条
  • [31] Non-contact Robust Respiration Detection By Using Radar-Depth Camera Sensor Fusion
    Zhao, Heng
    Gao, Xiaomeng
    Jiang, Xiaonan
    Hong, Hong
    Liu, Xiaoguang
    42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20, 2020, : 4183 - 4186
  • [32] Clustering Based Multi Sensor Data Fusion for Honeycomb Detection in Concrete
    Christoph Völker
    Parisa Shokouhi
    Journal of Nondestructive Evaluation, 2015, 34
  • [33] Multi sensor data fusion approach for automatic honeycomb detection in concrete
    Voelker, Christoph
    Shokouhi, Parisa
    NDT & E INTERNATIONAL, 2015, 71 : 54 - 60
  • [34] Clustering Based Multi Sensor Data Fusion for Honeycomb Detection in Concrete
    Voelker, Christoph
    Shokouhi, Parisa
    JOURNAL OF NONDESTRUCTIVE EVALUATION, 2015, 34 (04) : 1 - 10
  • [35] LiDAR and Camera Calibration using Motions Estimated by Sensor Fusion Odometry
    Ishikawa, Ryoichi
    Oishi, Takeshi
    Ikeuchi, Katsushi
    2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2018, : 7342 - 7349
  • [36] Sensor Fusion of Depth Camera and Ultrasound Data for Obstacle Detection and Robot Navigation
    Forouher, Dariush
    Besselmann, Marvin Grosse
    Maehle, Erik
    2016 14TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV), 2016,
  • [37] Obstacle detection by multi-sensor fusion of a laser scanner and depth camera
    Saleem, Zainab
    Long, Philip
    Huq, Saif
    McAfee, Marion
    2023 11TH INTERNATIONAL CONFERENCE ON CONTROL, MECHATRONICS AND AUTOMATION, ICCMA, 2023, : 13 - 18
  • [38] Multimedia sensor fusion for intelligent camera control
    Goodridge, SG
    Kay, MG
    MF '96 - 1996 IEEE/SICE/RSJ INTERNATIONAL CONFERENCE ON MULTISENSOR FUSION AND INTEGRATION FOR INTELLIGENT SYSTEMS, 1996, : 655 - 662
  • [39] Infrared and Camera Fusion Sensor for Indoor Positioning
    Martin-Gorostiza, Ernesto
    Garcia-Garrido, Miguel A.
    Pizarro, Daniel
    Torres, Patricia
    Ocana Miguel, Manuel
    Salido-Monzu, David
    2019 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN), 2019,
  • [40] Defect Detection in Concrete Structures Based on Characteristics of Hammer Reaction Force and Apparent Stiffness of Concrete
    Shoda, Koki
    Kasahara, Jun Younes Louhi
    An, Qi
    Yamashita, Atsushi
    IEEE ACCESS, 2025, 13 : 25325 - 25338