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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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