Comprehensive Sensitivity and Cross-Factor Variance Analysis-Based Multi-Objective Design Optimization of a 3-DOF Hybrid Magnetic Bearing
Zhijia Jin, Xiaodong Sun, Yingfeng Cai, Jianguo Zhu, Gang Lei, Youguang Guo
Abstract
Multi-degree-of-freedom (MDOF) magnetic bearings have been widely investigated and designed for various applications. However, a new design magnetic bearing cannot be directly used without optimization due to the not relatively excellent performance. Besides, there may be a lack of consideration of the interaction of parameters in the design process. Hence, in this article, a three-degree-of-freedom hybrid magnetic bearing (THMB) is optimized as an example. First, a comprehensive sensitivity analysis is carried out to show the relationship between the parameters and optimization objectives in detail. Second, a cross-factor variance analysis is considered due to the possibility of parameter interaction. And then, a hierarchical multi-objective optimization structure is used with the Kriging model and the non-dominated Sorting Genetic Algorithm II (NSGA II). The simulation results verify the validity of the proposed method, and the prototype is under manufacture for further evaluation.