Constantine Tarawneh – constantine.tarawneh@utrgv.edu
University Transportation Center for Railway Safety
University of Texas Rio Grande Valley
Edinburg, Texas, 78539
United States
Popular version of 3aPA4 – Preventing Hot Bearing Derailments via Wireless Onboard Condition Monitoring
Presented at the 187th ASA Meeting
Read the abstract at https://eppro01.ativ.me//web/index.php?page=IntHtml&project=ASAFALL24&id=3770628
–The research described in this Acoustics Lay Language Paper may not have yet been peer reviewed–
The 2023 train derailment that occurred in East Palestine, OH, brought attention to the limitations of the detectors currently used in the industry. 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 wayside detection 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, as it did in East Palestine, OH. Multiple comprehensive 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.
Video 1. Vibration and noise emitted from train bearings.
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 vibrations and acoustics signatures, as shown in Video 1, which can also be used to determine the severity and location of failure. This is accomplished in three levels of analysis where Level 1 determines the bearing condition based on the vibration levels within the bearing as compared to a maximum vibration threshold for healthy bearings. In Level 2, the vibration signature is analyzed to identify the defective component within the bearing, and Level 3 estimates the size of the defect based on a developed correlation that relates the vibration levels to defect size.
To demonstrate this process, Figure 1 provides the vibration and temperature profiles for two bearings. Examining the vibration profile, the vibration levels within bearing R7 exceed the maximum threshold for healthy bearings 730 hours into the test, thus indicating a defective bearing. At the same time, the operating temperature of that bearing never exceeded the normal operating range, which would suggest that the bearing is healthy. Upon teardown and visual inspection, we found severe damage to the bearing components at the raceways, as pictured in Figure 2. Despite severe damage all around the bearing inner ring (cone), the operating temperature did not indicate any abnormal behavior.
Figure 1: Vibration and temperature profiles of two railroad bearings showcasing how vibration levels within the bearings can indicate the development of defects while operating temperature does not exhibit any abnormal behavior.
Figure 1: Vibration and temperature profiles of two railroad bearings showcasing how vibration levels within the bearings can indicate the development of defects while operating temperature does not exhibit any abnormal behavior.
Figure 2: Picture of the damage that developed within bearing R7 (refer to Figure 1). Interestingly, the bearing inner ring (cone) had severe damage and a crack that the vibration levels picked up but not the operating temperature.
We believe that vibration-based sensors can provide proactive monitoring of bearing conditions affording rail operators ample time to detect the onset of bearing failure and schedule non-disruptive maintenance. Our work aims to continue to optimize these new methods and help the rail industry deploy these technologies to advance rail safety and efficiency. Moreover, this research program has had an extraordinary transformative impact from the local to the national level by training hundreds of engineers from underrepresented backgrounds and positioning them for success in industry, government, and higher education.