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A Non-intrusive Fault Diagnosis System For Robotic Platforms

  • The increasing complexity of tasks that are required to be executed by robots demands higher reliability of robotic platforms. For this, it is crucial for robot developers to consider fault diagnosis. In this study, a general non-intrusive fault diagnosis system for robotic platforms is proposed. A mini-PC is non-intrusively attached to a robot that is used to detect and diagnose faults. The health data and diagnosis produced by the mini-PC is then standardized and transmitted to a remote-PC. A storage device is also attached to the mini-PC for data logging of health data in case of loss of communication with the remote-PC. In this study, a hybrid fault diagnosis method is compared to consistency-based diagnosis (CBD), and CBD is selected to be deployed on the system. The proposed system is modular and can be deployed on different robotic platforms with minimum setup.

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Metadaten
Document Type:Conference Object
Language:English
Parent Title (English):Travé-Massuyès, Sztyber (Eds.): Proceedings of the 29th International Workshop on Principles of Diagnosis, co-located with 10th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS 2018), Warsaw, Poland, 27-30 August, 2018
URL:https://nbn-resolving.org/urn:nbn:de:0074-2289-2
Publisher:CEUR-WS.org
Date of first publication:2018/12/23
Departments, institutes and facilities:Fachbereich Informatik
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2018/05/28