Bridge Coating Inspection Based on Two-Stage Automatic Method and Collision-Tolerant Unmanned Aerial System

Automation in Construction（2022）SCI 1区

Cited 10|Views21

Abstract

Regular inspection of antirust coating is a vital approach to prevent steel bridges from corrosion. However, most existing coating inspection methods rely on inefficient manual examination with non-destructive testing (NDT) instruments. This study proposes a collision-tolerant unmanned aerial system (UAS) and the corresponding two-stage examination approach for bridge coating inspection. The contributions are as follows: (1) The UAS for coating inspection is designed with unique benefits including collision tolerance, non-GPS positioning, and NDT-based contact inspection. (2) Aiming at the problem that the GPS-based positioning method that existing UASs used is invalid in the close-range inspection for steel bridges because the GPS signal is blocked near steel bridges, a pseudo GPS navigation method using ultra-wideband (UWB) beacon is adopted to provide positioning data for the UAS. (3) To detect surface coating defects and coating thickness information in the inspection, a two-stage coating inspection method combining vision-based detection and contact-based measurement is proposed, in which surface defects of the coating are detected using a lightweight anchor-free network in real-time and then coating thickness around the defected area is measured with NDT method based on magnetic eddy current. The proposed method can detect the surface defects including coating spalling, fading, and hollowing in stage 1, and measure the coating thickness in stage 2. Experiments on an in-service bridge show the measured coating thickness error between the proposed method and manual inspection is less than 5%, which verifies the practicability and high precision of the proposed method.

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Key words

Bridge coating,Collision tolerance UAS,Non-destructive testing,Mechanical arm,Deep learning

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