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dc.contributor.authorSai, Samavedam Aditya
dc.contributor.authorVenkatesh, Sridharan Naveen
dc.contributor.authorDhanasekaran, Seshathiri
dc.contributor.authorBalaji, Parameshwaran Arun
dc.contributor.authorSugumaran, Vaithiyanathan
dc.contributor.authorLakshmaiya, Natrayan
dc.contributor.authorParamasivam, Prabhu
dc.date.accessioned2023-11-14T14:34:56Z
dc.date.available2023-11-14T14:34:56Z
dc.date.issued2023-07-26
dc.description.abstractThe suspension system is of paramount importance in any automobile. Thanks to the suspension system, every journey benefits from pleasant rides, stable driving and precise handling. However, the suspension system is prone to faults that can significantly impact the driving quality of the vehicle. This makes it essential to find and diagnose any faults in the suspension system and rectify them immediately. Numerous techniques have been used to identify and diagnose suspension faults, each with drawbacks. This paper’s proposed suspension fault detection system aims to detect these faults using deep transfer learning techniques instead of the time-consuming and expensive conventional methods. This paper used pre-trained networks such as Alex Net, ResNet-50, Google Net and VGG16 to identify the faults using radar plots of the vibration signals generated by the suspension system in eight cases. The vibration data were acquired using an accelerometer and data acquisition system placed on a test rig for eight different test conditions (seven faulty, one good). The deep learning model with the highest accuracy in identifying and detecting faults among the four models was chosen and adopted to find defects. The results state that VGG16 produced the highest classification accuracy of 96.70%.en_US
dc.identifier.citationSai, Venkatesh, Dhanasekaran, Balaji, Sugumaran, Lakshmaiya, Paramasivam. Transfer Learning Based Fault Detection for Suspension System Using Vibrational Analysis and Radar Plots. Machines. 2023;11(8)en_US
dc.identifier.cristinIDFRIDAID 2187805
dc.identifier.doi10.3390/machines11080778
dc.identifier.issn2075-1702
dc.identifier.urihttps://hdl.handle.net/10037/31787
dc.language.isoengen_US
dc.publisherMDPIen_US
dc.relation.journalMachines
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleTransfer Learning Based Fault Detection for Suspension System Using Vibrational Analysis and Radar Plotsen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)