Condition monitoring of train wheels using a cost-effective smart rail pad
type: CreativeWork
description: The present study focuses on the condition monitoring of train wheels utilizing an 3D printed rail pad that is embedded with widely available accelerometers and a strain gauge. This smart rail pad was used on a heavy haul railway line to monitor train wheels by identifying any wheel defects and measuring the respective wheel loads. A series of laboratory material tests were conducted on various 3D printing materials to access the right material for the smart rail pad. Dynamic and static loading tests were carried out to determine whether the 3D printed rail pads can withstand the typical forces exerted by a passing train. Field tests were done to determine the performance of the smart rail pads in operational conditions. Results indicated that the smart rail pads were able to identify 60 % of the wheel flats and able to measure the wheel loads by comparing it to the control measurements. Nonetheless, the smart rail pads presented a good correlation between the measured wheel loads and the true values, while the identification of wheel flats was influenced by the low sampling rate of the system.
abstract: The present study focuses on the condition monitoring of train wheels utilizing an 3D printed rail pad that is embedded with widely available accelerometers and a strain gauge. This smart rail pad was used on a heavy haul railway line to monitor train wheels by identifying any wheel defects and measuring the respective wheel loads. A series of laboratory material tests were conducted on various 3D printing materials to access the right material for the smart rail pad. Dynamic and static loading tests were carried out to determine whether the 3D printed rail pads can withstand the typical forces exerted by a passing train. Field tests were done to determine the performance of the smart rail pads in operational conditions. Results indicated that the smart rail pads were able to identify 60 % of the wheel flats and able to measure the wheel loads by comparing it to the control measurements. Nonetheless, the smart rail pads presented a good correlation between the measured wheel loads and the true values, while the identification of wheel flats was influenced by the low sampling rate of the system.
language: en
keywords: Condition monitoring, Additive manufacturing, Smart materials, Wheel flats, Wheel-rail contact force, UCTD
date published: 2022
date modified: 2026-07-24T03:52:45Z
provider: University of Pretoria
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Pretoria

PropertyValue
property ID: Handle
value: http://hdl.handle.net/2263/84010