DOI: 10.5937/jaes13-6909
This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions.
Volume 13 article 314 pages: 71-78
The goal of the
predictive condition monitoring of planetary power transmissions in pellet
mills is to indicate deterioration in the condition of the power transmissions before
the actual failure occurs. In many cases, the defect does not cause an
immediate interruption of the process. If this is the case, the defective part
can be replaced or repaired during normal, scheduled maintenance periods,
provided that the defect has been found in a sufficiently early stage. The most
common causes of failure of rotary machines are faults in bearings, the stator
and the rotor. There are many methods for the predictive condition monitoring
of rotary machines. The analysis can be based on different measured
quantities.These include, for example, temperature, current, magnetic flux
density and vibration. The basic design idea is to create a measurement and
data collection system for condition monitoring in which the data analyses and
decision-making are based on fuzzy logic programming. In this paper, a low-cost
optimal micro configuration for measurement and condition monitoring of data
collection system of pellet mills power transmission is presented. The system
is based on PIC (Programmable Interface Controller) microcontrollers and
represents the complete solution for condition monitoring regarding vibration,
temperature and rpm measurement. The microcontroller based system also has an
integrated function with control application based on fuzzy logic.
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