Identification of dynamic loads on structural component with artificial neural networks

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dc.identifier.uri http://dx.doi.org/10.15488/15975
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/16101
dc.contributor.author Altun, Osman
dc.contributor.author Zhang, Danyang
dc.contributor.author Siqueira, Renan
dc.contributor.author Wolniak, Philipp
dc.contributor.author Mozgova, Iryna
dc.contributor.author Lachmayer, Roland
dc.date.accessioned 2024-01-19T08:31:31Z
dc.date.available 2024-01-19T08:31:31Z
dc.date.issued 2020
dc.identifier.citation Altun, O.; Zhang, D.; Siqueira, R.; Wolniak, P.; Mozgova, I. et al.: Identification of dynamic loads on structural component with artificial neural networks. In: Procedia Manufacturing 52 (2020), S. 181-186. DOI: https://doi.org/10.1016/j.promfg.2020.11.032
dc.description.abstract Enhancing structural components by implementing sensors offers great potential regarding condition monitoring for lifetime analysis, predictive maintenance and automatic adaptation to environmental conditions. This article describes an approach to determining the operational forces applied to the front suspension arm of a car using strain gauges. Since suspension arms are components with free-form surfaces, an analytical calculation of applied forces by means of measured strains is not feasible. Hence, artificial neural networks are applied to approximate the functional relationship. The results reveal how artificial neural networks can be applied to identify load conditions on structural components and, therefore, deliver essential data for condition monitoring. eng
dc.language.iso eng
dc.publisher Amsterdam [u.a.] : Elsevier
dc.relation.ispartofseries Procedia Manufacturing 52 (2020)
dc.rights CC BY-NC-ND 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0
dc.subject Artificial neural networks eng
dc.subject Condition monitoring eng
dc.subject Load Identification eng
dc.subject Sensor integration eng
dc.subject Smart components eng
dc.subject.classification Konferenzschrift ger
dc.subject.ddc 620 | Ingenieurwissenschaften und Maschinenbau
dc.title Identification of dynamic loads on structural component with artificial neural networks eng
dc.type Article
dc.type Text
dc.relation.essn 2351-9789
dc.relation.doi https://doi.org/10.1016/j.promfg.2020.11.032
dc.bibliographicCitation.volume 52
dc.bibliographicCitation.firstPage 181
dc.bibliographicCitation.lastPage 186
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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