In the paper, an innovative wireless system for
press ram stress monitoring will be presented as component of a
decision support system for predictive maintenance. This system
involves low power consumption wireless nodes and energy
harvesting techniques to gain autonomy for the whole solution.
The monitoring systems output signals serve to extract and
generate “virtual sensor” signals. These represent actual load
and stress situations on locations that are crucial for machine
stability but are inaccessible for real measurement or even buried
inside the frame structure. In addition, the monitoring system is
embedded into a networked environment of an e-maintenance
cloud, linking a variety of information sources like enterprise
resource planning.
