Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A Prognostic Model Based on DBN and Diffusion Process for Degrading Bearing
Changhua Hu, Hong Pei, Xiaosheng Si, et al.
IEEE Transactions on Industrial Electronics (2019) Vol. 67, Iss. 10, pp. 8767-8777
Closed Access | Times Cited: 149

Showing 1-25 of 149 citing articles:

Health status assessment and remaining useful life prediction of aero-engine based on BiGRU and MMoE
Yong Zhang, Yuqi Xin, Zhi‐Wei Liu, et al.
Reliability Engineering & System Safety (2021) Vol. 220, pp. 108263-108263
Closed Access | Times Cited: 164
Multicellular LSTM-based deep learning model for aero-engine remaining useful life prediction
Sheng Xiang, Yi Qin, Jun Luo, et al.
Reliability Engineering & System Safety (2021) Vol. 216, pp. 107927-107927
Closed Access | Times Cited: 146
Transfer learning algorithms for bearing remaining useful life prediction: A comprehensive review from an industrial application perspective
Jiaxian Chen, Ruyi Huang, Zhuyun Chen, et al.
Mechanical Systems and Signal Processing (2023) Vol. 193, pp. 110239-110239
Closed Access | Times Cited: 101
Condition Monitoring of Industrial Electric Machines: State of the Art and Future Challenges
Sang Bin Lee, G.C. Stone, Jose A. Antonino‐Daviu, et al.
IEEE Industrial Electronics Magazine (2020) Vol. 14, Iss. 4, pp. 158-167
Open Access | Times Cited: 124
Adaptive Weighted Signal Preprocessing Technique for Machine Health Monitoring
Bingchang Hou, Dong Wang, Yi Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2020) Vol. 70, pp. 1-11
Closed Access | Times Cited: 80
Cascade Convolutional Neural Network With Progressive Optimization for Motor Fault Diagnosis Under Nonstationary Conditions
Fei Wang, Ruonan Liu, Qinghua Hu, et al.
IEEE Transactions on Industrial Informatics (2020) Vol. 17, Iss. 4, pp. 2511-2521
Closed Access | Times Cited: 78
A Risk-Averse Remaining Useful Life Estimation for Predictive Maintenance
Chuang Chen, Ningyun Lu, Bin Jiang, et al.
IEEE/CAA Journal of Automatica Sinica (2021) Vol. 8, Iss. 2, pp. 412-422
Closed Access | Times Cited: 76
Averaged Bi-LSTM networks for RUL prognostics with non-life-cycle labeled dataset
Yong Yu, Changhua Hu, Xiaosheng Si, et al.
Neurocomputing (2020) Vol. 402, pp. 134-147
Closed Access | Times Cited: 72
Autoencoder Quasi-Recurrent Neural Networks for Remaining Useful Life Prediction of Engineering Systems
Yiwei Cheng, Kui Hu, Jun Wu, et al.
IEEE/ASME Transactions on Mechatronics (2021) Vol. 27, Iss. 2, pp. 1081-1092
Closed Access | Times Cited: 63
Artificial Intelligence Enhanced Two-Stage Hybrid Fault Prognosis Methodology of PMSM
Baoping Cai, Zhengda Wang, Hongmin Zhu, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 18, Iss. 10, pp. 7262-7273
Closed Access | Times Cited: 57
A hybrid LSTM-KLD approach to condition monitoring of operational wind turbines
Yueqi Wu, Xiandong Ma
Renewable Energy (2021) Vol. 181, pp. 554-566
Open Access | Times Cited: 56
Hybrid remaining useful life prediction method. A case study on railway D-cables
Yu Zang, Wei Shangguan, Baigen Cai, et al.
Reliability Engineering & System Safety (2021) Vol. 213, pp. 107746-107746
Closed Access | Times Cited: 55
A reliability evaluation model of rolling bearings based on WKN-BiGRU and Wiener process
Le Dai, Junyu Guo, Jia-Lun Wan, et al.
Reliability Engineering & System Safety (2022) Vol. 225, pp. 108646-108646
Closed Access | Times Cited: 51
A contrastive learning framework enhanced by unlabeled samples for remaining useful life prediction
Ziqian Kong, Xiaohang Jin, Zhengguo Xu, et al.
Reliability Engineering & System Safety (2023) Vol. 234, pp. 109163-109163
Closed Access | Times Cited: 21
Box-Cox transformation based state-space modeling as a unified prognostic framework for degradation linearization and RUL prediction enhancement
Jie Liu, Bingchang Hou, Ming Lu, et al.
Reliability Engineering & System Safety (2024) Vol. 244, pp. 109952-109952
Closed Access | Times Cited: 13
A hybrid method combining Lévy process and neural network for predicting remaining useful life of rotating machinery
Shuai Lv, Shujie Liu, Hongkun Li, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102490-102490
Closed Access | Times Cited: 10
Accelerated degradation testing for lifetime analysis considering random effects and the influence of stress and measurement errors
Yang Li, Haifeng Gao, Hongtian Chen, et al.
Reliability Engineering & System Safety (2024) Vol. 247, pp. 110101-110101
Closed Access | Times Cited: 10
Artificial intelligence enhanced fault prediction with industrial incomplete information
Xiaoyan Shao, Baoping Cai, Zhexian Zou, et al.
Mechanical Systems and Signal Processing (2024) Vol. 224, pp. 112063-112063
Closed Access | Times Cited: 9
Residual Convolution Long Short-Term Memory Network for Machines Remaining Useful Life Prediction and Uncertainty Quantification
Wenting Wang, Yaguo Lei, Tao Yan, et al.
Journal of Dynamics Monitoring and Diagnostics (2021) Vol. 1, Iss. 1, pp. 2-8
Open Access | Times Cited: 53
Joint training of a predictor network and a generative adversarial network for time series forecasting: A case study of bearing prognostics
Hao Lü, Vahid Barzegar, Venkat Pavan Nemani, et al.
Expert Systems with Applications (2022) Vol. 203, pp. 117415-117415
Open Access | Times Cited: 35
Remaining Useful Life Estimation for Rolling Bearings Using MSGCNN-TR
Dong Guo, Zhi Cao, Hongyong Fu, et al.
IEEE Sensors Journal (2022) Vol. 22, Iss. 24, pp. 24333-24343
Closed Access | Times Cited: 27
Prognosis for stochastic degrading systems with massive data: A data-model interactive perspective
Tianmei Li, Hong Pei, Xiaosheng Si, et al.
Reliability Engineering & System Safety (2023) Vol. 237, pp. 109344-109344
Closed Access | Times Cited: 20
Bearing remaining useful life prediction with an improved CNN-LSTM network using an artificial gorilla troop optimization algorithm
Yonghua Li, Zhe Chen, Chaoqun Hu, et al.
Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability (2024)
Closed Access | Times Cited: 6
A novel gear RUL prediction method by diffusion model generation health index and attention guided multi-hierarchy LSTM
Xinping Chen
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 6
Review of Intelligent Modeling for Sintering Process Under Variable Operating Conditions
Jie Hu, Hongxiang Li, Junyong Liu, et al.
Processes (2025) Vol. 13, Iss. 1, pp. 180-180
Open Access
Page 1 - Next Page

Scroll to top