Research of Bridge Crack Detecting System Based on Machine Vision

Peng Fei Yang; Chang Wang

doi:10.4028/www.scientific.net/AMR.466-467.1197

Paper Titles

Remote Monitoring System for Unattended Electromechanical Equipment Based on Internet
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Research and Development of Solar Energy Automatic Bird Expeller Device
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Design of Fault Diagnosis Expert System for Certain Type of Aircraft Electrical Power
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The Visualization of Electromagnetic Environment for Weapon Equipments
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Research of Bridge Crack Detecting System Based on Machine Vision
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Flight Control Law Design via Pole Placement
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Predictive Control Based on Fuzzy Expert PID Tuning Control
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Design 3D Thermo-Mechanical Structures with Multidisciplinary Topology Optimization
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Speed-Regulation System of PMLSM Based on BP Neural Network PID Control
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Research of Bridge Crack Detecting System Based on Machine Vision

Abstract:

Aiming at the difficulty in crack detecting for bridges, a wireless crack detecting system based on machine vision and RC model helicopter was designed and realized. This system used a wireless camera to capture the surface images of bridges from the direction of below, then images were transmitted to the host computer by 2.4 GHz wireless communication. Edge image of crack can be gained after the image processing program carried out smoothing filtering, adaptive binary and edge extraction for original images of bridge. Image processing program adopted Hough transform to extract the characteristic parameters of bridge crack in edge images including length, width, shape and location of crack. The result of accuracy verification test shows that the relative error of this system was in the range of ±5% and it satisfied the requirements of early crack detecting for bridges.