Currently, railroad bearing temperatures are monitored using wayside infrared devices known as hot-box detectors (HBDs). HBDs take a snapshot of the bearing temperature at designated wayside detection sites which, depending on the track, may be spaced as far apart as 65 km (∼40 mi). Even though these devices have significantly reduced the number of derailments since their implementation, their discrete nature and limited accuracy prevents them from being utilized as a bearing health monitoring system. Future technologies are focusing on continuous temperature tracking of bearings. Since placing sensors directly on the bearing cup is not feasible due to cup indexing during service, the next logical location for such sensors is the bearing adapter. Understanding the thermal behavior of bearing adapters during operation is essential for sensor selection and placement within the adapter (e.g., typical temperature sensors have operating ranges of up to 125°C). To this end, this paper quantifies the steady-state heat transfer to the bearing adapter through a series of experiments and finite element analyses. The commercial software package ALGOR 20.3™ is used to conduct the thermal finite element analyses. Different heating scenarios are simulated with the purpose of obtaining the bearing adapter temperature distribution during normal and abnormal operating conditions. This paper presents an experimentally validated finite element thermal model which can be used to attain temperature distribution maps of bearing adapters in service conditions. These maps are useful for identifying ideal locations for sensor placement.
In the railroad industry, distressed bearings in service are primarily identified using wayside hot-box detectors (HBDs). Current technology has expanded the role of these detectors to monitor bearings that appear to “warm trend” relative to the average temperatures of the remainder of bearings on the train. Several bearings set-out for trending and classified as nonverified, meaning no discernible damage, revealed that a common feature was discoloration of rollers within a cone (inner race) assembly. Subsequent laboratory experiments were performed to determine a minimum temperature and environment necessary to reproduce these discolorations and concluded that the discoloration is most likely due to roller temperatures greater than 232 °C (450 °F) for periods of at least 4 h. The latter finding sparked several discussions and speculations in the railroad industry as to whether it is possible to have rollers reaching such elevated temperatures without heating the bearing cup (outer race) to a temperature significant enough to trigger the HBDs. With this motivation, and based on previous experimental and analytical work, a thermal finite element analysis (FEA) of a railroad bearing pressed onto an axle was conducted using ALGOR 20.3™. The finite element (FE) model was used to simulate different heating scenarios with the purpose of obtaining the temperatures of internal components of the bearing assembly, as well as the heat generation rates and the bearing cup surface temperature. The results showed that, even though some rollers can reach unsafe operating temperatures, the bearing cup surface temperature does not exhibit levels that would trigger HBD alarms.
Steel cleanliness is of the utmost importance in the production of tapered roller bearings used in the railroad industry. Impurities in the steel can make it vulnerable to fatigue initiation because they act as stress concentration sites in the fabricated parts, especially when these impurities are located in regions of susceptibility for rolling contact fatigue (RCF). Impurities present near the rolling surfaces (e.g., raceways in bearings) are referred to as subsurface inclusions. These subsurface inclusions make the steel susceptible to the initiation of fatigue cracks that can propagate towards the surface leaving a cavity called a "spall". Spalls occurring on the rolling surfaces of bearings can have detrimental effects that may lead to overheated bearings, loss of full service life, and in extreme cases, can lead to derailments if not addressed in-service by early detection methods. The study presented in this paper investigates the effects of subsurface inclusions present beneath the surface of the bearing cup (outer ring) and cone (inner ring) raceways. New bearing components were scanned using a unique ultrasonic technique in order to detect and identify potentially detrimental subsurface inclusions present in the RCF regions of the rolling surfaces. Two service life tests of these components were then carried out: one to examine subsurface inclusions found on cone raceways, and one to explore subsurface inclusions present on cup raceways. The test results indicate that the service life of components containing subsurface inclusions is reduced compared to controls for which no subsurface inclusions were detected. Moreover, subsurface inclusions on bearing cups appear to accelerate spall development relative to those present in bearing cones. This paper summarizes the findings of the experimental study performed on ultrasonically scanned bearing components, and emphasizes the need to establish more refined methods to inspect railroad rolling stock. These results are anticipated to be of great value to fatigue life prediction models relevant to the railroad industry.
A general spheroidal coordinate separation-of-variables solution is developed for the determination of the acoustic pressure distribution near the surface of a rigid spheroid for a monofrequency incident acoustic field of arbitrary character. Calculations are presented, for both the prolate and oblate geometries, demonstrating the effects of incident field orientation and character (plane-wave, spherical wave, cylindrical wave, and focused beam) on the resultant acoustic pressure distribution.
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