Schweizer, Nicolai ; Pongrac, Ivan (2022)
Semi-Autonomous Device for Visual Inspection of Vacuum Beamlines of Particle Accelerators.
8th International Particle Accelerator Conference. Copenhagen, Denmark (14.05.2017-19.05.2017)
doi: 10.26083/tuprints-00020318
Conference or Workshop Item, Secondary publication, Publisher's Version
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Item Type: | Conference or Workshop Item |
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Type of entry: | Secondary publication |
Title: | Semi-Autonomous Device for Visual Inspection of Vacuum Beamlines of Particle Accelerators |
Language: | English |
Date: | 2022 |
Place of Publication: | Darmstadt |
Year of primary publication: | 2017 |
Publisher: | Joint Accelerator Conferences Website |
Book Title: | Proceedings of the 8th International Particle Accelerator Conference |
Series: | International Particle Accelerator Conference |
Series Volume: | 8 |
Event Title: | 8th International Particle Accelerator Conference |
Event Location: | Copenhagen, Denmark |
Event Dates: | 14.05.2017-19.05.2017 |
DOI: | 10.26083/tuprints-00020318 |
Corresponding Links: | |
Origin: | Secondary publication service |
Abstract: | Due to the closed structure of ultra-high vacuum beamline systems, a visual inspection of the internal pipe is hardly feasible. For instance, when opening the accelerator vacuum system, an endoscope can be used to inspect the internals. However, this proves to be impractical in case of large, curved accelerator vacuum systems with complex geometries. It is more efficient to open the system only at one or two locations and to use a mobile semi-autonomous inspection device with optical imaging. A mobile robot is currently under development in our laboratory for the planned heavy ion synchrotron SIS100 at FAIR. A multitude of vacuum chamber types with different height levels as well as gaps must be traversed reliably by the robot. We present a modular wheel-based mobile robot prototype with joints between the modules which let the robot climb to different height levels by lifting the modules successively. |
Status: | Publisher's Version |
URN: | urn:nbn:de:tuda-tuprints-203184 |
Classification DDC: | 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering |
Divisions: | 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Robotics (from 01.08.2022 renamed Control Methods and Intelligent Systems) |
Date Deposited: | 14 Jan 2022 08:10 |
Last Modified: | 20 Mar 2023 12:24 |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/20318 |
PPN: | 490518923 |
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