上海交通大学学报 ›› 2024, Vol. 58 ›› Issue (3): 352-360.doi: 10.16183/j.cnki.jsjtu.2022.440
收稿日期:
2022-11-04
修回日期:
2023-02-10
接受日期:
2023-03-03
出版日期:
2024-03-28
发布日期:
2024-03-28
通讯作者:
胡 雄,博士,教授;E-mail:作者简介:
孙志伟(1994-),博士生,研究方向为港航设备自动检测与智能信息处理.
基金资助:
SUN Zhiwei1, HU Xiong1(), DONG Kai1, SUN Dejian1, LIU Yang2
Received:
2022-11-04
Revised:
2023-02-10
Accepted:
2023-03-03
Online:
2024-03-28
Published:
2024-03-28
摘要:
岸桥起升减速箱轴承的健康状况对港口生产安全具有重要意义.针对岸桥变工况的工作条件,提出一种起升减速箱轴承的剩余使用寿命(RUL)预测框架.首先,对工作载荷进行离散化,并确定工况边界.然后,利用长短时记忆(LSTM)网络模型预测载荷和相应的运行工况.其次,以维纳过程为基础,建立了考虑不同工况下退化率和跳变系数的状态退化函数.最后,利用工况激活粒子滤波(CAPF)方法预测轴承退化状态和RUL.采用NetCMAS系统采集的上海某港口起升减速箱轴承全寿命数据验证了所提出的预测框架.与其他3种预测模式比较表明,所提出的框架能够在变工况条件下获得更准确的退化状态和RUL预测.
中图分类号:
孙志伟, 胡雄, 董凯, 孙德建, 刘洋. 基于LSTM-CAPF框架的岸桥起升减速箱轴承寿命预测方法[J]. 上海交通大学学报, 2024, 58(3): 352-360.
SUN Zhiwei, HU Xiong, DONG Kai, SUN Dejian, LIU Yang. RUL Prediction Method for Quay Crane Hoisting Gearbox Bearing Based on LSTM-CAPF Framework[J]. Journal of Shanghai Jiao Tong University, 2024, 58(3): 352-360.
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