Improving Freight Train Wheel Monitoring with Smart Sensors
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Abstract
Onboard monitoring of freight car axleboxes enhances safety, reduces maintenance costs, and improves track conditions by preventing secondary damage. Installing wireless sensors on freight cars without a nearby power source should be cost-effective, given the large quantities involved. To address this, a new wireless smart sensor node has been deployed. The sensor automatically recognizes stable operating conditions, detects wheel rotational speed from vibrations, performs real-time condition monitoring, and transmits the results to the cloud. This study outlines the smart sensor concept and the pilot field test conducted with real freight cars. The results demonstrate the ability to estimate wheel rotational speed from vibrations and the potential for detecting wheel out-of-roundness (OOR) using a newly developed condition indicator for low-power real-time operations.
How to Cite
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Predictive Maintenance, Freight Railways, Wheel Out-of-Roundness, Onboard Monitoring, Edge Processing, Smart Sensors, Vibration Analysis, Edge AI, Axlebox Monitoring
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