RABIT: implementation, performance validation and integration with other robotic platforms for improved management of bridge decks

RABIT: implementation, performance validation and integration with other robotic platforms for... Accurate condition assessment and monitoring of concrete bridge deck deterioration progression requires both use of multiple nondestructive evaluation (NDE) technologies and automation in data collection and analysis. RABIT (robotics assisted bridge inspection tool) for bridge decks enables fully autonomous data collection at rates three or more times higher than it is typically done by a team of five inspectors using manual NDE technologies. The system concentrates on the detection and characterization of three most common internal deterioration and damage types: rebar corrosion, delamination, and concrete degradation. For that purpose, RABIT implements four NDE technologies: electrical resistivity (ER), ground-penetrating radar (GPR), impact echo (IE) and ultrasonic surface waves (USW) method. High productivity and higher spatial data resolution are achieved through the use of large sensor arrays or multiple probes for the four NDE methods. RABIT surveys also complement visual inspection by collecting high resolution images of the deck surface, which can be used for crack mapping and documentation of deck spalling, previous repairs, etc. The NDE technologies are used in a complementary way to enhance the overall condition assessment, certainty regarding the detected deterioration and better identification of the primary cause of deterioration. RABIT’s components, operation, field implementation and validation, as well as future integration with a robotic platform for minimally invasive rehabilitation, are described. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Intelligent Robotics and Applications Springer Journals

RABIT: implementation, performance validation and integration with other robotic platforms for improved management of bridge decks

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Publisher
Springer Singapore
Copyright
Copyright © 2017 by Springer Nature Singapore Pte Ltd.
Subject
Computer Science; Artificial Intelligence (incl. Robotics); Control, Robotics, Mechatronics; User Interfaces and Human Computer Interaction; Manufacturing, Machines, Tools; Electronics and Microelectronics, Instrumentation
ISSN
2366-5971
eISSN
2366-598X
D.O.I.
10.1007/s41315-017-0027-5
Publisher site
See Article on Publisher Site

Abstract

Accurate condition assessment and monitoring of concrete bridge deck deterioration progression requires both use of multiple nondestructive evaluation (NDE) technologies and automation in data collection and analysis. RABIT (robotics assisted bridge inspection tool) for bridge decks enables fully autonomous data collection at rates three or more times higher than it is typically done by a team of five inspectors using manual NDE technologies. The system concentrates on the detection and characterization of three most common internal deterioration and damage types: rebar corrosion, delamination, and concrete degradation. For that purpose, RABIT implements four NDE technologies: electrical resistivity (ER), ground-penetrating radar (GPR), impact echo (IE) and ultrasonic surface waves (USW) method. High productivity and higher spatial data resolution are achieved through the use of large sensor arrays or multiple probes for the four NDE methods. RABIT surveys also complement visual inspection by collecting high resolution images of the deck surface, which can be used for crack mapping and documentation of deck spalling, previous repairs, etc. The NDE technologies are used in a complementary way to enhance the overall condition assessment, certainty regarding the detected deterioration and better identification of the primary cause of deterioration. RABIT’s components, operation, field implementation and validation, as well as future integration with a robotic platform for minimally invasive rehabilitation, are described.

Journal

International Journal of Intelligent Robotics and ApplicationsSpringer Journals

Published: Jul 17, 2017

References

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