Axle Bearings: A Series of Wise Decisions from Manufacturing to Monitoring

The first and most important function of a train wheel bearing is to reduce friction and allow for smoother rotation between the rotating shaft and the part that supports the rotation. The second function is to protect the part that supports the rotation and maintain the correct position for the rotating shaft. This helps in extending the life of the train. 

Axle Bearings

Many factors are contributing to the overall load applied upon the rolling stock axle bearings. There is the load caused by rail joints, switches, and sometimes wheel flats, in addition to the static and dynamic radial loads of vehicle weight. Moreover, when the train runs on curved rails or in a snaking motion, the bearings receive axial loads due to the lateral movement. When all of these loads are combined, they form complicated enforcement of pressure upon the axle bearings. Keeping this in mind, it is essential to design the bearings to endure such conditions and comply with the standard dimensional requirements of the axle journal and bearing box geometry. 

Bearing Failure

Due to all these applied forces and the main functionalities of axle bearings, any bearing failure can lead to very serious derailments, potentially causing human casualties, severe disruption in the operation of the network, damage to the tracks, and unnecessary costs. Therefore, wise decisions should be taken from the start to choose the right bearings manufactured, considering all these forces, high-load capacity characteristics, low friction, a wide operating temperature range, and better corrosion resistance. It is also noted to choose the right condition-based monitoring tools that support the axle bearings with their role. 

Condition-Based Monitoring

Condition-based monitoring is a maintenance strategy that allows operators to monitor the actual condition of the bearings to decide upon their health and any potential disruptions that need to be addressed by studying their changes. The data collected by implementing an algorithm based on historical observations of the bearings can contribute greatly in taking preventive, prognostic, and trend decisions, which leads to increased life of the bearings, lower maintenance needed, optimizing the functionality of the bearing, and reducing the risk of bearing failure. It also has other advantages as allowing the scheduling of preventive and corrective actions at an optimal time, reducing the risk of any future consequences, improving the equipment reliability, improving the safety of workers, and increasing the time needed between maintenance, which means less cost. 

Enhancing Safety

Axle bearings have a critical role in enhancing the safety of the train, which is the main concern of railway operators. Therefore, it is imperative to give more attention to the manufacturing process, where all the previously mentioned factors are considered. In addition to that, it is fundamental to have the right condition-based monitoring tool that helps to boost the functionality of the bearings.