Online Model for Suspension Faults Diagnostics Using IoT and Analytics

Publication Type:

Journal Article

Authors:

Kokane, P.; Bagavathi Sivakumar, P.

Source:

Advances in Intelligent Systems and Computing, Springer Verlag, Volume 870, p.145-154 (2019)

ISBN:

9789811326721

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058334198&doi=10.1007%2f978-981-13-2673-8_17&partnerID=40&md5=f13a26aeea6b900b0b6ea1d6ff9dda20

Keywords:

Active suspension, Active suspension systems, Evolution of technology, Fault detection, Fault prediction, Faulting, Faults diagnostics, Internet of things, Learning systems, Maintenance cost, Mechanical assembly, Online modeling, Suspension system, Suspensions (components), Suspensions (fluids)

Abstract:

Automobile world and technologies are advancing with rapid pace. A lot of resources are pouring into evolution of technologies considering safety, ride, and comfort of passengers. Suspension systems have also changed from just a mechanical assembly to active suspensions with multi-sensors for enhancing the actuations. Detecting faults in the suspension system early and categorizing them not only reduce the maintenance cost but add comfort and safety. In this paper, suspension faults have been studied and investigated. Approaches toward detecting suspension faults have been discussed. Internet of things and analytics-based online model for suspension fault detection are proposed. © Springer Nature Singapore Pte Ltd. 2019.

Notes:

cited By 0; Conference of International Conference on Advanced Computing, Networking and Informatics, ICANI 2018 ; Conference Date: 22 February 2018 Through 24 February 2018; Conference Code:221629

Cite this Research Publication

P. Kokane and P. Sivakumar, B., “Online Model for Suspension Faults Diagnostics Using IoT and Analytics”, Advances in Intelligent Systems and Computing, vol. 870, pp. 145-154, 2019.

 
             
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