Research on the System Level Vibration State Correlation Model for Tracked Vehicles Fusing Transmission Mechanisms
For vibration prediction of tracked vehicles,a system-level vibration state correlation model fu-sing transmission mechanisms is proposed.Firstly,based on the structure of tracked vehicles,the vibration transmission path is clarified,and a multi-level correlation model architecture is determined.Then,the correlation model is constructed using deep learning approaches and optimized by selecting key position ex-citation load parameters.Finally,real vehicle vibration dataset is used for vibration state prediction.Com-pared with the method without fusing transmission mechanisms,the proposed correlation model fusing transmission mechanisms improves the prediction accuracy of six vibration indicators,which verifies the ef-fectiveness of the vibration prediction method fusing transmission mechanism.
NETL
NSTL
万方数据
