中国舰船研究2025，Vol.20Issue(2)：107-117,11.DOI:10.19693/j.issn.1673-3185.03962
基于多任务门控网络的滚动轴承寿命预测方法
A rolling bearing life prediction method based on multi-task gated networks
摘要
Abstract
[Objective]To achieve the remaining life prediction of bearings in ship mechanical equipment,a multi-task gated networks prediction model based on the Bidirectional Gated Recurrent Unit(BiGRU),Vari-ational Autoencoder(VAE),and Multi-gate Mixture-of-Experts(MMoE)is proposed.[Methods]First,the time-domain features of the bearing signals are calculated to characterize the basic degradation trends in the monitoring data.Then,a multi-task gated networks prediction model composed of bearing Health State(HS)assessment and Remaining Useful Life(RUL)prediction subtasks is established.In the subtasks,BiGRU and VAE are used to extract the degradation information from the trend signals of the time-domain features,and then MMoE is utilized to adaptively separate the distinctive features of the subtasks.Finally,the effectiveness is verified on the XJTU-SY bearing dataset.[Results]The results show that,compared with classic time-series data prediction models such as Long Short Term Memory(LSTM),the multi-task gated networks pre-diction model has higher prediction accuracy,with the error metrics Mean Absolute Error(MAE)and Root Mean Square Error(RMSE)improved by 62.5%and 67.81%respectively.[Conclusion]The proposed method can achieve the prediction of the remaining life of bearings and has certain reference value for the health management and intelligent operations and maintenance(O&M)of ship mechanical equipment.关键词
船舶设备/轴承/剩余寿命预测/多任务门控网络预测模型Key words
ship equipment/bearing(machine parts)/remaining life prediction/multi-task gated network prediction model分类
交通工程引用本文复制引用
宋浏阳,郑传浩,金烨,林天骄,韩长坤,王华庆..基于多任务门控网络的滚动轴承寿命预测方法[J].中国舰船研究,2025,20(2):107-117,11.基金项目
国家自然科学基金面上项目(52375076) （52375076）
北京市科技新星计划(20240484559) （20240484559）
