Heavy duty wheels are used in applications 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 the most critical assembly phase, since it is completely made by an operator and a contamination of the link area may happen. Furthermore the presence of rust on the hub surface can contribute to worsen the adherence interface, reducing the wheel operating life. In this scenario, a fault detection procedure to be use at the end of the manufacturing process has been developed. The fault detection procedure is based on vibration processing techniques. In this paper, several wheels with rust presence on the hub have been manufactured ‘ad hoc’ with anomalies similar to the ones that can really be originated. Signal processing techniques have been used in order to detect the presence of rust; in particular, cyclostationary theory is applied to extract information from the frequency/order domain of the processed signals. Indicators based on cyclostationary theory can be considered as the key parameters to be adopted in a monitoring test station at the end of the production line.

Use of cyclostationary analysis for rust detection on the hub of heavy duty wheels

MUCCHI, Emiliano;D'ELIA, Gianluca;DALPIAZ, Giorgio
2014

Abstract

Heavy duty wheels are used in applications 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 the most critical assembly phase, since it is completely made by an operator and a contamination of the link area may happen. Furthermore the presence of rust on the hub surface can contribute to worsen the adherence interface, reducing the wheel operating life. In this scenario, a fault detection procedure to be use at the end of the manufacturing process has been developed. The fault detection procedure is based on vibration processing techniques. In this paper, several wheels with rust presence on the hub have been manufactured ‘ad hoc’ with anomalies similar to the ones that can really be originated. Signal processing techniques have been used in order to detect the presence of rust; in particular, cyclostationary theory is applied to extract information from the frequency/order domain of the processed signals. Indicators based on cyclostationary theory can be considered as the key parameters to be adopted in a monitoring test station at the end of the production line.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2303026
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