Image-Based Monitoring of Open Gears of Movable Bridges for Condition Assessment and Maintenance Decision Making

    Authors

    M. Gul; F. N. Catbas;H. Hattori

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Abbreviated Journal Title

    J. Comput. Civil. Eng.

    Keywords

    Structural health monitoring; Imaging techniques; Cameras; Bridges; Neural networks; Maintenance; Decision making; Structural health; monitoring; Image processing; Computer vision; Video camera; Condition; Edge detection; Movable bridge; Neural network; Open gear; Maintenance; DAMAGE ASSESSMENT; INFLUENCE LINES; NETWORK; SYSTEMS; UNIT; Computer Science, Interdisciplinary Applications; Engineering, Civil

    Abstract

    Movable bridges are unique structures due to the complex interaction between their structural, mechanical, and electrical systems with an intricate interrelation creating several challenges related to operation and maintenance. Continuous monitoring of the critical parts of these structures is essential to track and evaluate their performance for improving maintenance operations and reducing the associated costs. Open gears are one of the most critical components of movable bridges. Proper and regular maintenance of these gears is vitally important to ensure a safe, reliable, and cost-effective operation. In this study, a practical and low-cost monitoring approach is presented to track the lubrication level in an open gear of a movable bridge by using video cameras. Two unique indices are developed for monitoring of the open gear by investigating two different image processing methods in a comparative fashion. The first methodology is based on an edge detection algorithm that utilizes a Sobel gradient operator to determine the edges in the open gear image. A lubrication index (LI) based on the edge detection results is defined and extracted to determine the lubrication level. The second methodology employs a fuzzy neural network-based approach to define a lubrication anomaly parameter (LAP) for assessing the lubrication level. The analysis results from the real-life application show that both methodologies successfully identify the lubrication level of the movable bridge's open gear.

    Journal Title

    Journal of Computing in Civil Engineering

    Volume

    29

    Issue/Number

    2

    Publication Date

    1-1-2015

    Document Type

    Article

    Language

    English

    First Page

    11

    WOS Identifier

    WOS:000349978500002

    ISSN

    0887-3801

    Share

    COinS