Mitigating train derailments through proactive condition monitoring of rolling stock

Distinguished Series: Academic Track

with Constantine Tarawneh,
University of Texas Rio Grande Valley

October 10, 2025 – 2:30 PM
Torgersen Hall 2150

The 2023 East Palestine, OH, train derailment brought attention to the limitations of current wayside detectors. Typically, the health of train bearings is monitored intermittently through wayside temperature detection systems that can be as far as 40 miles apart. Nonetheless, catastrophic bearing failure is often sudden and develops rapidly. Current systems are reactive in nature and depend on significant temperature increases above ambient. Thus, when these systems are triggered, train operators rarely have enough time to react before a derailment occurs. Studies have shown that the temperature difference between healthy and faulty bearings is not statistically meaningful until the onset of catastrophic failure. Thus, temperature alone is an insufficient metric for health monitoring. Over the past two decades, we have demonstrated vibration-based solutions for wireless onboard condition monitoring of train components to address this problem. Early stages of bearing failure are reliably detected via vibration signatures, which can also be used to determine the severity and location of failure. Vibration-based sensors can provide proactive monitoring of bearing conditions affording rail operators ample time to detect the onset of failure and schedule non-disruptive maintenance.

Constantine Tarawneh is a Professor of Mechanical Engineering at the University of Texas Rio Grande Valley (UTRGV) where he worked since 2003. He obtained his MS and Ph.D. degrees from the University of Nebraska-Lincoln (UNL) in 1999 and 2003, respectively. He founded the University Transportation Center for Railway Safety (UTCRS) in 2013 and the NSF CREST Center for Multidisciplinary Research Excellence in Cyber-Physical Infrastructure System (MECIS) in 2021 and serves as the Founding Director for both Centers. He also serves as the Sr. Associate Dean for the College of Engineering and Computer Science since 2016. His various research and educational activities have resulted in $44 Million in funding from federal, industry, state, private, and local sources. He has more than 23 years of experience conducting a variety of railroad research with emphasis on advanced bearing condition monitoring techniques. He received 36 teaching, mentoring, and research awards highlighted by the UT System Regents’ Outstanding Teaching Award in 2009. In Fall of 2017, he was appointed as the Louis A. Beecherl, Jr. Endowed Professor in Engineering, and in Fall 2023, he was inducted into the UTRGV Academy of Distinguished Teachers. To date, he has mentored and supervised over 1300 undergraduate and graduate students.