Fault detection in heavy duty wheels by advanced vibration processing techniques and lumped parameter modeling

•Condition monitoring of heavy duty wheels based on vibration analysis.•Synchronous average and cyclostationary theory have been accounted.•The signal signatures are explained taking advantage of a lumped parameter model.•Evaluation of pass–fail reference values based on Tukey׳s non-statistical method.

Heavy duty wheels are used in applications such as automatic vehicles and are mainly composed of a polyurethane tread glued to a cast iron hub. In the manufacturing process, the adhesive application between tread and hub is a critical assembly phase, since it is completely made by an operator and a contamination of the bond area may happen. Furthermore, the presence of rust on the hub surface can contribute to worsen the adherence interface, reducing the operating life. In this scenario, a quality control procedure for fault detection to be used at the end of the manufacturing process has been developed. This procedure is based on vibration processing techniques and takes advantages of the results of a lumped parameter model. Indicators based on cyclostationarity can be considered as key parameters to be adopted in a monitoring test station at the end of the production line due to their not deterministic characteristics.