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Dynamic Modeling and Sound (Noise) Diagnostics of Robot Gearboxes for Fault Assessments
Mälardalens högskola, Institutionen för datavetenskap och elektronik.
State Scientific and Research Institute of Information Infrastructure, Lviv, Ukraine .
2005 (engelsk)Inngår i: Proceedings of SIMS 2005 - Scandinavian Conference on Simulation and Modeling, 2005Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
2005.
HSV kategori
Identifikatorer
URN: urn:nbn:se:mdh:diva-2736OAI: oai:DiVA.org:mdh-2736DiVA, id: diva2:115399
Konferanse
SIMS 2005 - Scandinavian Conference on Simulation and Modeling
Tilgjengelig fra: 2008-11-11 Laget: 2008-11-11 Sist oppdatert: 2015-10-12bibliografisk kontrollert
Inngår i avhandling
1. Fault Diagnosis of Industrial Machines using Sensor Signals and Case-Based Reasoning
Åpne denne publikasjonen i ny fane eller vindu >>Fault Diagnosis of Industrial Machines using Sensor Signals and Case-Based Reasoning
2009 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
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.

sted, utgiver, år, opplag, sider
Västerås: Mälardalens högskola, 2009. s. 186
Serie
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 76
HSV kategori
Forskningsprogram
Datavetenskap
Identifikatorer
urn:nbn:se:mdh:diva-6539 (URN)978-91-86135-32-4 (ISBN)
Disputas
2009-09-18, Pathos, Mälardalens högskola, R-2, Västerås, 13:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2009-07-13 Laget: 2009-07-06 Sist oppdatert: 2018-01-13bibliografisk kontrollert

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