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24 July 2001 Residue detection for real-time removal of paint from metallic surfaces
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Abstract
Paint stripping from large steel ships and other metallic surfaces is a major environmental safety, cost, and operational challenge in effectively and efficiently maintaining and refurbishing large structures. Environmental concerns are greatly limiting the possible options. As a result, a hybrid system composed of a waterjet with water recycling and robotic mobile manipulators with scanning bridges has become the leading form of paint stripping and was constructed by various manufacturers to address this need. The application of such scanning bridges is slow and their access is constrained by the complex shape of the ship hull and various features on the surface. To overcome these limitations, a robotic system that is called UltraStrip (UltraStrip Systems, Inc., Stuart, FL) is developed. This system uses magnetic wheels to attach the stripper to the structure and travel on it while performing paint stripping. To assure efficient paint stripping feedback data is required to control the travel speed by monitoring the paint thickness before and during the stripping process. Efforts at JPL are currently underway to develop the required feedback capability to assure effective paint stripping. Various possible sensors were considered and issues that can affect the sensitivity, reliability and applicability of the sensors are being investigated with emphasis on measuring the initial conditions of the paint. Issues that affect the sensory data in dynamic conditions are addressed while providing real-time real feedback for the control of the paint stripper speed of travel.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yoseph Bar-Cohen, Xiaoqi Bao, Benjamin P. Dolgin, and Neville I. Marzwell "Residue detection for real-time removal of paint from metallic surfaces", Proc. SPIE 4335, Advanced Nondestructive Evaluation for Structural and Biological Health Monitoring, (24 July 2001); https://doi.org/10.1117/12.434165
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