Intelligent identification method for whole aero-engine connection stiffness

• Main Authors: Meijiao Qu, Guo Chen, Kaiyong Zhang
• Format: Article
• Language: English
• Published: JVE International 2018-05-01
• Series: Journal of Vibroengineering
• Subjects: aero-engine; whole engine vibration; model updating; connection stiffness; intelligent identification
• Online Access: https://www.jvejournals.com/article/18864

A novel intelligent identification method for determining connection stiffness values of the aircraft engine vibration model is proposed. Firstly, a dynamic finite element model of an aero-engine is established. The stiffness values of supports and mountings are taken as the connection parameters to be optimized, and then the natural frequencies of the whole machine are obtained under different connection stiffness values by finite element simulations. The regression function, which is from the stiffness to the natural frequency, is constructed in the support vector machines method. Then, the genetic algorithm is applied to a multi-objective optimization. Based on the real natural frequencies (which can be obtained by a modal test), a fitness function of multi-objective optimization of genetic algorithm is established. Using the real number coding method, the connection stiffness values of the whole machine are finally identified. An aero-engine rotor tester with casing is taken as an example to verify the method. According to the results of a modal test, the stiffness values of the supports and mountings are identified, and the results show the method effectiveness.