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Dynamic Modeling and Sound (Noise) Diagnostics of Robot Gearboxes for Fault Assessments
Mälardalen University, Department of Computer Science and Electronics.
State Scientific and Research Institute of Information Infrastructure, Lviv, Ukraine .
2005 (English)In: Proceedings of SIMS 2005 - Scandinavian Conference on Simulation and Modeling, 2005Conference paper, Published paper (Refereed)
Abstract [en]

Some gear faults in industrial robots can during operation be recognized as abnormal noise peaks coming from the gearbox. A library of such recordings has been assembled in order to automate fault diagnosis of the robots. A computer records sound from the gearbox and compare the new recordings with recordings stored in the library. The result of the comparison is a diagnosis of the condition of the robot. This paper proposes an extension of the sound library by incorporating model based reasoning. A dynamic model of the gearbox in the drive system has been constructed and gear vibrations on the force level are extracted from the model. These vibrations are projected onto the sound recordings with a statistical vibration diagnostic parameter known as the Crest Factor CF.

Place, publisher, year, edition, pages
2005.
National Category
Other Engineering and Technologies
Identifiers
URN: urn:nbn:se:mdh:diva-2736OAI: oai:DiVA.org:mdh-2736DiVA, id: diva2:115399
Conference
SIMS 2005 - Scandinavian Conference on Simulation and Modeling
Available from: 2008-11-11 Created: 2008-11-11 Last updated: 2015-10-12Bibliographically approved
In thesis
1. Fault Diagnosis of Industrial Machines using Sensor Signals and Case-Based Reasoning
Open this publication in new window or tab >>Fault Diagnosis of Industrial Machines using Sensor Signals and Case-Based Reasoning
2009 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Industrial machines sometimes fail to operate as intended. Such failures can be more or less severe depending on the kind of machine and the circumstances of the failure. E.g. the failure of an industrial robotcan cause a hold-up of an entire assembly line costing the affected company large amounts of money each minute on hold. Research is rapidly moving forward in the area of artificial intelligence providing methods for efficient fault diagnosis of industrial machines. The nature of fault diagnosis of industrial machines lends itself naturally to case-based reasoning. Case-based reasoning is a method in the discipline of artificial intelligence based on the idea of assembling experience from problems and their solutions as ”cases” for reuse in solving future problems. Cases are stored in a case library, available for retrieval and reuse at any time.By collecting sensor data such as acoustic emission and current measurements from a machine and representing this data as the problem part of a case and consequently representing the diagnosed fault as the solution to this problem, a complete series of the events of a machine failure and its diagnosed fault can be stored in a case for future use.

Place, publisher, year, edition, pages
Västerås: Mälardalens högskola, 2009. p. 186
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 76
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-6539 (URN)978-91-86135-32-4 (ISBN)
Public defence
2009-09-18, Pathos, Mälardalens högskola, R-2, Västerås, 13:00 (English)
Opponent
Supervisors
Available from: 2009-07-13 Created: 2009-07-06 Last updated: 2018-01-13Bibliographically approved

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Citation style
  • apa
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