Bearing Acoustic Monitor


Track IQ - RailBAM system is a "Bearing Acoustic Monitor' (BAM) that monitors the acoustic signature of each axle bearing passing the system at line speed.

RailBAM technology can accurately and reliably identify the presence of defects in bearings and rank the bearing severity and fault type. 

Through use of RailBAM, network downtime due to Hot Bearing Alarm (HBA) events is greatly reduced. This is because RailBAM is an early warning system and can detect problem bearings months in advance of any heat generation due to the defect.

In addition, RailBAM enables predictive maintenance as maintainers can monitor (trend) the bearing condition and optimize the timing of a vehicle’s removal from service. This allows for improved maintenance planning and in many cases customers have been able to extended bearing life.

RailBAM's principle of operation is based on analysing sound characteristics emitted by bearing faults. A bearing fault excites a structural response in the bearing and the sound radiated from the housing is sampled.

Proprietary signal processing techniques allow the bearing fault signal to be isolated other noise (e.g. wheel noise), enabling fault identification and classification.

RailBAM is applicable to Package and Axle Box Bearings of all load classes and all bearing manufacturers. If new bearing types enter service, RailBAM system configuration can be updated to correctly analyse data for these bearings.  

In conjunction with the FleetONE database, bearing defects can be monitored and trended over time. This ensures that bearings that deteriorate at different rates are effectively managed and fault severity levels provide clear indicators as to which bearings in the Fleet require attention. 

The RailBAM Bearing Acoustic Monitor is designed for remote use in extreme conditions, therefore requiring minimal ongoing inspection and maintenance. Systems are installed and operational in hot arid zones such as Australia and United Arab Emirates, as well as in extreme cold and snowy environments such as Canada, Norway and China.

RailBAM has an autonomous self-monitoring capability to ensure that field equipment is functioning correctly. Component failures or warnings are identified during a system self-check, and system alerts can be sent to the system maintainer by email. This allows remote system monitoring and ensures the maintenance technicians understand equipment status before going to site, thus reducing time in the field.

There are over 130 RailBAM systems in operation world-wide, proving RailBAM's value as a core component of any railway's condition monitoring program.