基于粒子群算法优化的变速箱磨损损伤灰关联评估研究

Wear damage assessment of the gearbox based on PSO and grey relational theory

变速箱作为导弹发射车的关键传动部件之一,其故障状态直接影响到导弹发射车作战的可靠性和安全性。为准确评估导弹发射车变速箱的磨损损伤状态,选取变速箱的油液铁谱分析数据作为输入特征信息,基于灰关联理论建立了导弹发射车的变速箱损伤评估模型,并应用粒子群算法对该模型的分辨系数进行优化,提高了变速箱损伤评估的准确性。

The gearbox is one the key transmission components of the missile launching vehicle.Its fault status directly affects the reliability and safety of the missile launching vehicle on the war.In order to accurately assess the wear state of the missile launching vehicle,this paper built a gearbox wear damage assessment model based on the grey relational theory,selecting the Ferrogra-phy analyze data of oil.And the Particle Swarm Optimization(PSO)is used to optimize the model,which improved the accuracy of the assessment.