Life Prediction of Crossed Roller Bearings for Industrial Robots Based on FOA-GRNN Approach
Crossed roller bearings are widely used in industrial robots,and their service life directly affects the economic cost of industrial robots.In order to ensure the higher prediction accuracy of generalised regression neural network(GRNN),multiple swarm adaptive Drosophila optimisation algorithms(FOA)are used to optimise its expansion speed,and a life prediction method for cross roller bearings of industrial robots based on the FOA-GRNN method is constructed.The results of the study show that the prediction by FOA-GRNN method has high results.Compared with the separate FOA and GRNN methods,all the indicators using the FOA-GRNN method are the smallest,which verifies the effectiveness of the FOA-optimised GRNN method,and achieves the improvement of the efficiency and accuracy of the optimisation search.This research helps to improve the operating life of industrial robots and has high significance of energy saving.
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