Modeling and Optimization of Parameters in Condition Monitoring for Angular Misalignment Using the Desirability Concept and JAYA Algorithm
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Abstract
In high-precision machines, aligned close tolerance rotating part condition is vitally important. It is usual practice that machines are examined critically for aligned conditions at the time of installation. It is seen that it is subject slowly to misaligned conditions during the working period. In the Industry 4.0 revolution, condition monitoring of machines is one of the main priorities. In the present work, misalignment in rotating parts and its effects on the machine are studied to determine the lowest overall vibration level (OVL) and find influencing process parameters for OVL. The output vibration signals are obtained for the different misaligned conditions through experimental setup. The experimental layout is designed using the design of experiments, response surface methodology, and central composite design. Further analysis is carried out using Minitab 16 software. The process parameter considered for experiments is speed and angular misalignment. The corresponding performance values are obtained for speed range 500 to 2100 rpm and angular misalignment 0.01 to 0.08 mm/inch. The process parameters are optimized to obtain the lower value of OVL. ANOVA analysis showed that both speed and angular misalignment, along with square terms, is significant. The obtained lowest OVL value is 0.544 mm by the desirability concept, and it is further improved to 0.448 mm by the JAYA algorithm. The average error of implementation is less than 2 %.
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