The paper illustrates a new method to improve the reliability of condition monitoring systems for rolling mills gearboxes. In this context,as well as in many other industrial fields,one of the main problem is the definition of the proper thresholds to trigger a predictive maintenance intervention. The preliminary knowledge of system behaviour,when a failure is imminent,would obviously greatly ease this task. Since this operating condition cannot be easily investigated experimentally,numerical models of the system have been conceived and developed to predict bearing failure effects in several working conditions. The generated outputs (i.e. the vibration corresponding to different fault conditions associated with the main common failures of the transmission elements) will constitute a database useful to tune up and train the whole apparatus for the condition monitoring of the mechanical system.
Model-based training of a gearbox condition monitoring system
CINQUEMANI, SIMONE;ROSA, FRANCESCO;
2016-01-01
Abstract
The paper illustrates a new method to improve the reliability of condition monitoring systems for rolling mills gearboxes. In this context,as well as in many other industrial fields,one of the main problem is the definition of the proper thresholds to trigger a predictive maintenance intervention. The preliminary knowledge of system behaviour,when a failure is imminent,would obviously greatly ease this task. Since this operating condition cannot be easily investigated experimentally,numerical models of the system have been conceived and developed to predict bearing failure effects in several working conditions. The generated outputs (i.e. the vibration corresponding to different fault conditions associated with the main common failures of the transmission elements) will constitute a database useful to tune up and train the whole apparatus for the condition monitoring of the mechanical system.File | Dimensione | Formato | |
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