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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:

Bearing Remaining Useful Life Prediction Based on Regression Shapalet and Graph Neural Network
Xiaoyu Yang, Ying Zheng, Yong Zhang, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-12
Closed Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

Spatio-Temporal Fusion Attention: A Novel Approach for Remaining Useful Life Prediction Based on Graph Neural Network
Ziqian Kong, Xiaohang Jin, Zhengguo Xu, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-12
Closed Access | Times Cited: 72
Temporal multi-resolution hypergraph attention network for remaining useful life prediction of rolling bearings
Jinxin Wu, Deqiang He, Jiayi Li, et al.
Reliability Engineering & System Safety (2024) Vol. 247, pp. 110143-110143
Closed Access | Times Cited: 29
Remaining Useful Life Prediction Method Based on the Spatiotemporal Graph and GCN Nested Parallel Route Model
Liuyang Song, Ye Jin, Tianjiao Lin, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-12
Closed Access | Times Cited: 20
Health state assessment of bearing with feature enhancement and prediction error compensation strategy
Yong Zhang, Jiahua Sun, Jing Zhang, et al.
Mechanical Systems and Signal Processing (2022) Vol. 182, pp. 109573-109573
Open Access | Times Cited: 49
Few-Shot Bearing Fault Diagnosis via Ensembling Transformer-based Model with Mahalanobis Distance Metric Learning from Multiscale Features
Manh-Hung Vu, Van-Quang Nguyen, Thi-Thao Tran, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-18
Closed Access | Times Cited: 9
A Novel Methodology for Unsupervised Anomaly Detection in Industrial Electrical Systems
Marco Carratù, Vincenzo Gallo, Salvatore Dello Iacono, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-12
Open Access | Times Cited: 19
Local Enhancing Transformer With Temporal Convolutional Attention Mechanism for Bearings Remaining Useful Life Prediction
Huachao Peng, Bin Jiang, Zehui Mao, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-12
Closed Access | Times Cited: 18
Research on Digital Twin Driven Rolling Bearing Model-Data Fusion Life Prediction Method
Wentao Zhao, Chao Zhang, Jianguo Wang, et al.
IEEE Access (2023) Vol. 11, pp. 48611-48627
Open Access | Times Cited: 16
Vibration-based anomaly pattern mining for remaining useful life (RUL) prediction in bearings
Pooja Kamat, Satish Kumar, Rekha Sugandhi
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2024) Vol. 46, Iss. 5
Closed Access | Times Cited: 5
Prediction of Residual Life of Rolling Bearings Based on Multi-Scale Improved Temporal Convolutional Network (MITCN) Model
Kaiwen Xia, Q. Li, Liangliang Han, et al.
Machines (2025) Vol. 13, Iss. 2, pp. 137-137
Open Access
Explicit Representation and Customized Fault Isolation Framework for Learning Temporal and Spatial Dependencies in Industrial Processes
Pengyu Song, Chunhui Zhao, Biao Huang, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 3, pp. 2997-3011
Closed Access | Times Cited: 15
Causal dilated Convolution-Based residual DenseNet with channel attention for RUL prediction of rolling bearings
Jimeng Li, Wanmeng Ding, Weilin Mao, et al.
Measurement (2024) Vol. 235, pp. 115012-115012
Closed Access | Times Cited: 4
Remaining useful life prediction for stochastic deteriorating Devices: A direct approach via inverse degradation modeling
Tianmei Li, Zhenyu Cai, Zhaoju Zeng, et al.
Mechanical Systems and Signal Processing (2025) Vol. 228, pp. 112431-112431
Closed Access
A $T^{2}$-Tensor-Aided Multiscale Transformer for Remaining Useful Life Prediction in IIoT
Lei Ren, Zidi Jia, Xiaokang Wang, et al.
IEEE Transactions on Industrial Informatics (2022) Vol. 18, Iss. 11, pp. 8108-8118
Closed Access | Times Cited: 20
A remaining useful life prediction method based on time–frequency images of the mechanical vibration signals
Xianjun Du, Wenchao Jia, Ping Yu, et al.
Measurement (2022) Vol. 202, pp. 111782-111782
Closed Access | Times Cited: 20
A Lightweight and Adaptive Knowledge Distillation Framework for Remaining Useful Life Prediction
Lei Ren, Tao Wang, Zidi Jia, et al.
IEEE Transactions on Industrial Informatics (2022) Vol. 19, Iss. 8, pp. 9060-9070
Closed Access | Times Cited: 20
Remaining Useful Life Prediction and Uncertainty Quantification for Bearings Based on Cascaded Multiscale Convolutional Neural Network
Jialong He, Chenchen Wu, Wei Luo, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 73, pp. 1-13
Closed Access | Times Cited: 11
A bearing RUL prediction approach of vibration fault signal denoise modeling with Gate-CNN and Conv-Transformer encoder
Peng Huang, Yuanjin Wang, Yingkui Gu, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 066104-066104
Closed Access | Times Cited: 3
Virtual Sensor for Real-Time Bearing Load Prediction Using Heterogeneous Temporal Graph Neural Networks
Mengjie Zhao, Cees Taal, Stephan Baggerohr, et al.
PHM Society European Conference (2024) Vol. 8, Iss. 1, pp. 8-8
Open Access | Times Cited: 3
Convolution-Graph Attention Network With Sensor Embeddings for Remaining Useful Life Prediction of Turbofan Engines
Xiao Chen, Ming Zeng
IEEE Sensors Journal (2023) Vol. 23, Iss. 14, pp. 15786-15794
Closed Access | Times Cited: 10
Comprehensive Dynamic Structure Graph Neural Network for Aero-Engine Remaining Useful Life Prediction
Hongfei Wang, Zhuo Zhang, Xiang Li, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-16
Closed Access | Times Cited: 10
Multi-task learning mixture density network for interval estimation of the remaining useful life of rolling element bearings
Xin Wang, Yongbo Li, Khandaker Noman, et al.
Reliability Engineering & System Safety (2024) Vol. 251, pp. 110348-110348
Closed Access | Times Cited: 3
Hierarchical graph neural network with adaptive cross-graph fusion for remaining useful life prediction
Gang Wang, Yanan Zhang, Ming-Feng Lu, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 5, pp. 055112-055112
Closed Access | Times Cited: 8
Uncertainty Quantification and Interval Prediction of Equipment Remaining Useful Life Based on Semisupervised Learning
Hui Liu, Zhenyu Liu, Donghao Zhang, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 73, pp. 1-15
Closed Access | Times Cited: 8
A Node-Level PathGraph-Based Bearing Remaining Useful Life Prediction Method
Chaoying Yang, Jie Liu, Kaibo Zhou, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-10
Closed Access | Times Cited: 13
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