Long-term temporal attention neural network with adaptive stage division for remaining useful life prediction of rolling bearings
Author
Abstract
Suggested Citation
DOI: 10.1016/j.ress.2024.110218
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Liu, Lu & Song, Xiao & Zhou, Zhetao, 2022. "Aircraft engine remaining useful life estimation via a double attention-based data-driven architecture," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
- Miao, Mengqi & Yu, Jianbo & Zhao, Zhihong, 2022. "A sparse domain adaption network for remaining useful life prediction of rolling bearings under different working conditions," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
- Li, Guofa & Wei, Jingfeng & He, Jialong & Yang, Haiji & Meng, Fanning, 2023. "Implicit Kalman filtering method for remaining useful life prediction of rolling bearing with adaptive detection of degradation stage transition point," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
- Wang, Lei & Cao, Hongrui & Ye, Zhisheng & Xu, Hao, 2023. "Bayesian large-kernel attention network for bearing remaining useful life prediction and uncertainty quantification," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
- Cheng, Han & Kong, Xianguang & Wang, Qibin & Ma, Hongbo & Yang, Shengkang, 2022. "The two-stage RUL prediction across operation conditions using deep transfer learning and insufficient degradation data," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
- Li, Wanxiang & Shang, Zhiwu & Gao, Maosheng & Qian, Shiqi & Feng, Zehua, 2022. "Remaining useful life prediction based on transfer multi-stage shrinkage attention temporal convolutional network under variable working conditions," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
- Kong, Ziqian & Jin, Xiaohang & Xu, Zhengguo & Chen, Zian, 2023. "A contrastive learning framework enhanced by unlabeled samples for remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
- Zuo, Tao & Zhang, Kai & Zheng, Qing & Li, Xianxin & Li, Zhixuan & Ding, Guofu & Zhao, Minghang, 2023. "A hybrid attention-based multi-wavelet coefficient fusion method in RUL prognosis of rolling bearings," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
- Ni, Qing & Ji, J.C. & Feng, Ke & Zhang, Yongchao & Lin, Dongdong & Zheng, Jinde, 2024. "Data-driven bearing health management using a novel multi-scale fused feature and gated recurrent unit," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
- Hou, WanJun & Peng, Yizhen, 2023. "Adaptive ensemble gaussian process regression-driven degradation prognosis with applications to bearing degradation," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
- Bai, Rui & Noman, Khandaker & Feng, Ke & Peng, Zhike & Li, Yongbo, 2023. "A two-phase-based deep neural network for simultaneous health monitoring and prediction of rolling bearings," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Wang, Chen & Zhang, Liming & Chen, Ling & Tan, Tian & Zhang, Cong, 2025. "Remaining useful life prediction of nuclear reactor control rod drive mechanism based on dynamic temporal convolutional network," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
- Xiao, Xiaoqi & Zhang, Jianguo & Xu, Dan, 2025. "Contrastive domain-invariant generalization for remaining useful life prediction under diverse conditions and fault modes," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
- Han, Yan & Hu, Ailin & Huang, Qingqing & Zhang, Yan & Lin, Zhichao & Ma, Jinghua, 2025. "Sinkhorn divergence-based contrast domain adaptation for remaining useful life prediction of rolling bearings under multiple operating conditions," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
- Xu, Xinlei & Zhang, Junhui & Huang, Weidi & Yu, Bin & Lyu, Fei & Zhang, Xiaolong & Xu, Bing, 2024. "The loose slipper fault diagnosis of variable-displacement pumps under time-varying operating conditions," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Yang, Jing & Wang, Xiaomin, 2024. "Meta-learning with deep flow kernel network for few shot cross-domain remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
- Kim, Sunghyun & Seo, Yun-Ho & Park, Junhong, 2024. "Transformer-based novel framework for remaining useful life prediction of lubricant in operational rolling bearings," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
- Han, Yaoyao & Ding, Xiaoxi & Gu, Fengshou & Chen, Xiaohui & Xu, Minmin, 2025. "Dual-drive RUL prediction of gear transmission systems based on dynamic model and unsupervised domain adaption under zero sample," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
- Xu, Xiaobin & Zhou, Jiahao & Weng, Xu & Zhang, Zehui & He, Hong & Steyskal, Felix & Brunauer, Georg, 2024. "A novel evidence reasoning-based RUL prediction method integrating uncertainty information," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
- Liu, Yang & Zhou, Guangda & Zhao, Shujian & Li, Liang & Xie, Wenhua & Su, Bengan & Li, Yongwei & Zhao, Zhen, 2025. "A novel two-stage method via adversarial strategy for remaining useful life prediction of bearings under variable conditions," Reliability Engineering and System Safety, Elsevier, vol. 254(PA).
- Xu, Zhiqiang & Zhang, Yujie & Miao, Qiang, 2024. "An attention-based multi-scale temporal convolutional network for remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
- Yan, Jianhai & Ye, Zhi-Sheng & He, Shuguang & He, Zhen, 2024. "A feature disentanglement and unsupervised domain adaptation of remaining useful life prediction for sensor-equipped machines," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
- Xu, Dan & Xiao, Xiaoqi & Liu, Jie & Sui, Shaobo, 2023. "Spatio-temporal degradation modeling and remaining useful life prediction under multiple operating conditions based on attention mechanism and deep learning," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
- Yan, Jianhai & He, Zhen & He, Shuguang, 2023. "Multitask learning of health state assessment and remaining useful life prediction for sensor-equipped machines," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
- Yang, Shilong & Tang, Baoping & Wang, Weiying & Yang, Qichao & Hu, Cheng, 2024. "Physics-informed multi-state temporal frequency network for RUL prediction of rolling bearings," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
- Wang, Chen & Zhang, Liming & Chen, Ling & Tan, Tian & Zhang, Cong, 2025. "Remaining useful life prediction of nuclear reactor control rod drive mechanism based on dynamic temporal convolutional network," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
- Xu, Yuhui & Xia, Tangbin & Jiang, Yimin & Wang, Yu & Wang, Dong & Pan, Ershun & Xi, Lifeng, 2024. "A temporal partial domain adaptation network for transferable prognostics across working conditions with insufficient data," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
- Gao, Zhan & Jiang, Weixiong & Wu, Jun & Dai, Tianjiao & Zhu, Haiping, 2024. "Nonlinear slow-varying dynamics-assisted temporal graph transformer network for remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
- Han, Yan & Hu, Ailin & Huang, Qingqing & Zhang, Yan & Lin, Zhichao & Ma, Jinghua, 2025. "Sinkhorn divergence-based contrast domain adaptation for remaining useful life prediction of rolling bearings under multiple operating conditions," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
- Yang, Qichao & Tang, Baoping & Deng, Lei & Zhang, Xiaolong & Wu, Jinzhou, 2025. "A hybrid dual-frequency-informed spider net for RUL prognosis with adaptive IDP detection and outlier correction," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
- Wang, Xin & Li, Yongbo & Noman, Khandaker & Nandi, Asoke K., 2024. "Multi-task learning mixture density network for interval estimation of the remaining useful life of rolling element bearings," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
- Basora, Luis & Viens, Arthur & Chao, Manuel Arias & Olive, Xavier, 2025. "A benchmark on uncertainty quantification for deep learning prognostics," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
- Jiang, Deyin & Chen, Tianyu & Xie, Juanzhang & Cui, Weimin & Song, Bifeng, 2023. "A mechanical system reliability degradation analysis and remaining life estimation method——With the example of an aircraft hatch lock mechanism," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
- Chen, Chuanhai & Li, Bowen & Guo, Jinyan & Liu, Zhifeng & Qi, Baobao & Hua, Chunlei, 2022. "Bearing life prediction method based on the improved FIDES reliability model," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
- Liang, Pengfei & Tian, Jiaye & Wang, Suiyan & Yuan, Xiaoming, 2024. "Multi-source information joint transfer diagnosis for rolling bearing with unknown faults via wavelet transform and an improved domain adaptation network," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
More about this item
Keywords
Rolling Bearings; Reliability analysis; Remaining Useful Life Prediction; Temporal convolution; Attention;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:251:y:2024:i:c:s0951832024002916. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.