自动化与信息工程2025，Vol.46Issue(2)：54-62,9.DOI:10.12475/aie.20250208
多故障模式下的设备剩余使用寿命预测方法
Remaining Useful Life Prediction Method for Equipment under Multiple Failure Modes
单苏苏 1信明江1
作者信息
- 1. 五邑大学轨道交通学院,广东 江门 529020
- 折叠
摘要
Abstract
To address the issue where different failure modes of equipment have varying impacts on its service life and degradation trajectories when the equipment fails due to multiple failure modes,this paper proposes a multi-task branch model based on deep time-series clustering(DTC)to achieve failure mode identification and remaining useful life(RUL)prediction.First,DTC is employed to extract features from the input data and perform failure mode identification.Then,based on the DTC based failure mode identification results,the corresponding branch model is selected for RUL prediction.Experimental results on a turbofan engine simu-lation dataset demonstrate that,compared to models that do not consider multiple failure modes,the proposed model achieves higher RUL prediction accuracy,with the mean absolute percentage error reduced by 5.69%.关键词
剩余使用寿命/多故障模式/深度时间序列聚类/故障模式识别/分支预测器Key words
remaining useful life/multiple failure modes/deep time-series clustering/failure mode identification/branch predictor分类
计算机与自动化引用本文复制引用
单苏苏,信明江..多故障模式下的设备剩余使用寿命预测方法[J].自动化与信息工程,2025,46(2):54-62,9.
