With increasing complexity in the heavy duty construction equipment, early fault detection of certain components in the machine becomes more and more challenging due to too many fault codes generated when a failure occurs. The axle is one such component. The axle transfers driving torque from the transmission to the wheels and axle failure may result in costly downtime of construction equipment. To reduce service cost and to improve uptime, adequate condition monitoring based on sensor data from the axle is considered by for instance measuring vibrations on the axle. Further, the analysis of the data collected has been has been carried out using adequate signal processing methods. The results indicate that the vibration properties of the axle are relevant for early fault detection of the axle. Thus, the health of the axle may be continuously monitored on-board using the vibration information and if the axle health starts to degrade a service and/or repair may be scheduled well in advance of a potential axle failure and in that way the downtime of a machine may be reduced and costly replacements and repairs avoided.