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 method for rapidly evaluating reliability and predicting remaining useful life using two-dimensional convolutional neural network with signal conversion
Qibin Wang, Bo Zhao, Hongbo Ma, et al.
Journal of Mechanical Science and Technology (2019) Vol. 33, Iss. 6, pp. 2561-2571
Closed Access | Times Cited: 56

Showing 1-25 of 56 citing articles:

A comprehensive review on convolutional neural network in machine fault diagnosis
Jinyang Jiao, Ming Zhao, Jing Lin, et al.
Neurocomputing (2020) Vol. 417, pp. 36-63
Open Access | Times Cited: 403
Challenges and Opportunities of Deep Learning Models for Machinery Fault Detection and Diagnosis: A Review
Mohd Syahril Ramadhan Mohd Saufi, Zair Asrar Ahmad, M. Salman Leong, et al.
IEEE Access (2019) Vol. 7, pp. 122644-122662
Open Access | Times Cited: 226
An enhanced convolutional neural network for bearing fault diagnosis based on time–frequency image
Ying Zhang, Kangshuo Xing, Ruxue Bai, et al.
Measurement (2020) Vol. 157, pp. 107667-107667
Closed Access | Times Cited: 222
A Review on Deep Learning Applications in Prognostics and Health Management
Liangwei Zhang, Jing Lin, Bin Liu, et al.
IEEE Access (2019) Vol. 7, pp. 162415-162438
Open Access | Times Cited: 182
Deep multi-scale convolutional transfer learning network: A novel method for intelligent fault diagnosis of rolling bearings under variable working conditions and domains
Bo Zhao, Xianmin Zhang, Zhenhui Zhan, et al.
Neurocomputing (2020) Vol. 407, pp. 24-38
Closed Access | Times Cited: 139
An Intelligent Fault Diagnosis Method of Rolling Bearings Based on Short-Time Fourier Transform and Convolutional Neural Network
Qi Zhang, Linfeng Deng
Journal of Failure Analysis and Prevention (2023) Vol. 23, Iss. 2, pp. 795-811
Closed Access | Times Cited: 55
Challenges and Opportunities of AI-Enabled Monitoring, Diagnosis & Prognosis: A Review
Zhibin Zhao, Jingyao Wu, Tianfu Li, et al.
Chinese Journal of Mechanical Engineering (2021) Vol. 34, Iss. 1
Open Access | Times Cited: 98
Conditional GAN and 2-D CNN for Bearing Fault Diagnosis With Small Samples
J. N. Yang, Jie Liu, Jingsong Xie, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-12
Open Access | Times Cited: 82
A multi-ensemble method based on deep auto-encoders for fault diagnosis of rolling bearings
Xianguang Kong, Gang Mao, Qibin Wang, et al.
Measurement (2019) Vol. 151, pp. 107132-107132
Closed Access | Times Cited: 78
Prognostics and Health Management of Industrial Assets: Current Progress and Road Ahead
Luca Biggio, Iason Kastanis
Frontiers in Artificial Intelligence (2020) Vol. 3
Open Access | Times Cited: 69
Research on rolling bearing virtual-real fusion life prediction with digital twin
Wentao Zhao, Chao Zhang, Bin Fan, et al.
Mechanical Systems and Signal Processing (2023) Vol. 198, pp. 110434-110434
Open Access | Times Cited: 36
Remaining useful life prediction combined dynamic model with transfer learning under insufficient degradation data
Han Cheng, Xianguang Kong, Qibin Wang, et al.
Reliability Engineering & System Safety (2023) Vol. 236, pp. 109292-109292
Closed Access | Times Cited: 26
Temporal convolution-based transferable cross-domain adaptation approach for remaining useful life estimation under variable failure behaviors
Jichao Zhuang, Minping Jia, Yifei Ding, et al.
Reliability Engineering & System Safety (2021) Vol. 216, pp. 107946-107946
Closed Access | Times Cited: 52
Deep transfer learning based on dynamic domain adaptation for remaining useful life prediction under different working conditions
Han Cheng, Xianguang Kong, Qibin Wang, et al.
Journal of Intelligent Manufacturing (2021) Vol. 34, Iss. 2, pp. 587-613
Closed Access | Times Cited: 47
Remaining useful life prediction of rolling bearings based on Bayesian neural network and uncertainty quantification
Guang‐Jun Jiang, Jin‐Sen Yang, Tiancai Cheng, et al.
Quality and Reliability Engineering International (2023) Vol. 39, Iss. 5, pp. 1756-1774
Closed Access | Times Cited: 21
Non-destructive strength prediction of composite laminates utilizing deep learning and the stochastic finite element methods
Christos Nastos, Panagiotis Komninos, Dimitrios Zarouchas
Composite Structures (2023) Vol. 311, pp. 116815-116815
Open Access | Times Cited: 18
An Improved ResNet-1d with Channel Attention for Tool Wear Monitor in Smart Manufacturing
Liang Dong, Chensheng Wang, Guang Yang, et al.
Sensors (2023) Vol. 23, Iss. 3, pp. 1240-1240
Open Access | Times Cited: 16
RUL prediction based on GAM–CNN for rotating machinery
Xianjun Du, Wenchao Jia, Ping Yu, et al.
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2023) Vol. 45, Iss. 3
Closed Access | Times Cited: 16
Multisensor-based tool wear diagnosis using 1D-CNN and DGCCA
Yong Yin, Shuxin Wang, Jian Zhou
Applied Intelligence (2022) Vol. 53, Iss. 4, pp. 4448-4461
Closed Access | Times Cited: 25
A concise review on degradation of gun barrels and its health monitoring techniques
Deepak Kumar, Sahil Kalra, Mayank Jha
Engineering Failure Analysis (2022) Vol. 142, pp. 106791-106791
Open Access | Times Cited: 22
A deep neural network and Bayesian method based framework for all-terminal network reliability estimation considering degradation
Alex Davila-Frias, Nita Yodo, Trung Van Le, et al.
Reliability Engineering & System Safety (2022) Vol. 229, pp. 108881-108881
Open Access | Times Cited: 22
A Review of Remaining Useful Life Prediction Approaches for Mechanical Equipment
Yangyang Zhang, Liqing Fang, Ziyuan Qi, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 24, pp. 29991-30006
Closed Access | Times Cited: 15
Adaptive Feature Utilization With Separate Gating Mechanism and Global Temporal Convolutional Network for Remaining Useful Life Prediction
Pengcheng Xia, Yixiang Huang, Chengjin Qin, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 18, pp. 21408-21420
Closed Access | Times Cited: 14
Fault diagnosis of wind turbine based on multi-signal CNN-GRU model
Yang Chen, Xiaoxia Zheng
Proceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy (2023) Vol. 237, Iss. 5, pp. 1113-1124
Closed Access | Times Cited: 13
Multiscale Dynamic Weight Based Mixed Convolutional Neural Network for Fault Diagnosis of Rotating Machinery
Wenliao Du, Lingkai Yang, Xiaoyun Gong, et al.
IEEE Transactions on Instrumentation and Measurement (2025) Vol. 74, pp. 1-11
Closed Access
Page 1 - Next Page

Scroll to top