Prediction and Prognostics of Engineered Surface Failures through Sensing Technologies within Large Mobile Assets

Authors: Saeed, A., Khan, Z. and Rafik, T.

http://www.stle.org/files/Events/Annual_Meeting_and_Exhibition/files/Events/AM/Annual_Meeting/Meeting_Not_Open.aspx?hkey=be8b2521-e3cc-451b-abef-e818fd01b8e1

Start date: 21 May 2017

Publisher: Society of Tribologists and Lubrication Engineers

Place of Publication: USA

Large vehicles are usually subject to varying operational conditions during their service life. These operating conditions include highly saline and humid coastal conditions, hot and dry atmospheric environments containing sand and soil particulates and extreme operating temperatures.

These mobile assets endure structural degradation during post-operational storage. Large vehicles, which have been exposed to extreme operating conditions, exhibit various modes of structural degradation. Erosive wear in combination with corrosion leads to complex failures mechanism.

This research reports the failures of engineered surfaces during storage while these failures were essentially incubated during operation. To sustain structural integrity of large vehicles in storage, a framework based on sensing technology has been developed and implemented for monitoring, prediction and prognostics. This framework is condition-based that enables cost savings to relevant industries and replaces schedule-based maintenance approaches.

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