Research on Machine Learning-based Aero-engine Local Balancing Technology
Aiming at the low equilibrium efficiency and high cost caused by the traditional aero-engine local balancing technology,by collecting experimental data that had been successfully balanced,the artificial intelligence and machine learning methods of single random forest and multi-method fusion were adopted respectively.The relevant laws embedded in experimental data was deeply mined.The intelligent local balancing model of the aero-engine was established,and the intelligent prediction of the balanced weighting angles was realized.Based on the multi-method fusion of the local balancing technology model,all samples training prediction error was only 3.06 °,indicating the advantages of multi-method fusion.The intelligent dynamic equilibrium technology provided an important technical approach for the use and popularization of aero-engine equilibrium.
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