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    Vision-Based Quality Inspection in Robotic Welding
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    The article discusses the construction of a robotic vision system station intended for the measurement of selected parameters of the aluminium body. Due to the number of measured parameters and the complex shape of the controlled body, the vision system is positioned relative to the body with the use of an industrial robot. The robot realizes transition movements allowing the observation of few features on different surfaces of the body. Implementation of measurements using a camera and an industrial robot enables: assessing the surface condition, checking the presence of defects on surfaces, reading codes printed on surfaces, measuring the diameter of holes, etc. The paper describes the method of hardware integration, image acquisition method and measurement algorithms used in the implementation of measurements.
    Machine Vision
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    A planning system for efficient of robotic inspection of surface tolerances is presented. This is done using visual tracking of a manual polishing tool. The application that is studied is surface finishing of large ship propeller blades. The propeller blade is cast in in NiAl bronze and then adjusted by manual surface finishing. Robotic inspection is used to check the quality of the resulting surface using an high-accuracy RGBD-camera. To avoid time-consuming inspection of the entire propeller blade, the area affected by the manual adjustment is detected with a visual tracking system, which measures the motion of the manual tool using a particle filter and a CAD model of the tool. The main contribution of this work is the strategy for selecting camera views for the inspection robot. The algorithm employs Hotelling's T-squared distribution in a Principal Component Analysis to find efficient viewpoints. The approach is implemented with an industrial robot, a high-accuracy RGBD-camera, and a low-cost RGBD-camera. The system is validated in simulations and experiments, where a surface conditioned ship propeller blade is inspected.
    Visual inspection
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    Welding is a very important process in the industrial scenario, especially in the shipbuilding industry. Many researches employ robots to automate different welding process. This paper proposes a system for automated seam tracking, based on passive vision, to act as a data feedback to the automated robotic welding system, with quality and productivity gains in the process. Different cameras arrangements are presented and tested as the vision acquisition system in a commercial linear welding robot. A physical method and an algorithm to remove visual noises from images, produced by the GMAW welding process, are presented and the results discussed.
    Robot welding
    Machine Vision
    Monocular vision
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    Component (thermodynamics)
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