转子轴承系统结合部等效刚度识别

针对转子轴承结合面刚度难于确定的问题,提出一种有限元模态分析、试验模态分析与BP神经网络相结合的等效刚度识别方法。采用Abaqus有限元分析软件建立转子轴承系统的有限元分析模型并得到其固有频率;并对转子轴承系统进行试验模态分析,得到前四阶弯曲固有频率;最后通过BP神经网络对等效刚度和固有频率进行训练与识别。研究结果表明,转子轴承系统的径向等效刚度识别最大相对误差为1.75%,轴向等效刚度识别最大相对误差为5.43%。方法为机械结构结合部的参数识别提供了参考。

EQUIVALENT STIFFNESS IDENTIFICATION FOR JOINT OF ROTOR BEARING SYSTEM

Aimed at the difficulty in identifying the equivalent stiffness of rotor bearing joint,an equivalent stiffness identification method of combining finite element modal analysis,experimental modal analysis and back propagation neural network was proposed.Firstly,the finite element model analysis of a rotor bearing system was built with the Abaqus,and the respective natural frequencies were obtained.Secondly,the first four bending natural frequencies of the rotor bearing system were acquired with experimental modal analysis.Finally,the equivalent stiffness and natural frequencies were trained and identified by BP neural network.Research results showed that the maximum relative error of the radial and axial equivalent stiffness identification of the rotor bearing system were 1.75% and 5.43% respectively.The research work provides a reference for parametric identification on mechanical structure joint.