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OpenAlex Citation Counts

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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:

An image-based feature extraction method for fault diagnosis of variable-speed rotating machinery
Jung Ho Park, Yunhan Kim, Kyumin Na, et al.
Mechanical Systems and Signal Processing (2021) Vol. 167, pp. 108524-108524
Closed Access | Times Cited: 18

Showing 18 citing articles:

Explicit speed-integrated LSTM network for non-stationary gearbox vibration representation and fault detection under varying speed conditions
Yuejian Chen, Xuemei Liu, Meng Rao, et al.
Reliability Engineering & System Safety (2024), pp. 110596-110596
Closed Access | Times Cited: 16
Advancements in condition monitoring and fault diagnosis of rotating machinery: A comprehensive review of image-based intelligent techniques for induction motors
Omar AlShorman, Muhammad Irfan, Ra’ed Bani Abdelrahman, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 130, pp. 107724-107724
Open Access | Times Cited: 25
Application of Time-Frequency Analysis in Rotating Machinery Fault Diagnosis
Yihao Bai, Weidong Cheng, Weigang Wen, et al.
Shock and Vibration (2023) Vol. 2023, pp. 1-16
Open Access | Times Cited: 17
Weighted multi-order Viterbi algorithm (WMOVA): Instantaneous angular speed estimation under harsh conditions
Jinoh Yoo, Jongmin Park, Tae-Hyung Kim, et al.
Mechanical Systems and Signal Processing (2024) Vol. 211, pp. 111187-111187
Closed Access | Times Cited: 6
Physics-informed Gaussian Process Probabilistic Modeling with Multi-source Data for Prognostics of Degradation Processes
Chen Jiang, Teng Zhong, Hyunhee Choi, et al.
Reliability Engineering & System Safety (2025), pp. 110893-110893
Closed Access
MPARN: multi-scale path attention residual network for fault diagnosis of rotating machines
Hyeongmin Kim, Chan Hee Park, Chaehyun Suh, et al.
Journal of Computational Design and Engineering (2023) Vol. 10, Iss. 2, pp. 860-872
Open Access | Times Cited: 12
Discriminative feature learning and selection with label-induced sparse filtering for intelligent fault diagnosis of rotating machinery
Zhiqiang Zhang, Shuiqing Xu, Hongtian Chen
Mechanical Systems and Signal Processing (2023) Vol. 196, pp. 110338-110338
Closed Access | Times Cited: 9
A Review of Fault Diagnosis Methods for Rotating Machinery Using Infrared Thermography
Rongcai Wang, Xianbiao Zhan, Huajun Bai, et al.
Micromachines (2022) Vol. 13, Iss. 10, pp. 1644-1644
Open Access | Times Cited: 14
Applications of improved linear chirplet time frequency representation to Machine bearing fault analysis
Junbo Long, Haibin Wang, Hongshe Fan, et al.
Measurement (2023) Vol. 209, pp. 112460-112460
Closed Access | Times Cited: 8
Two-dimensional composite multi-scale time–frequency reverse dispersion entropy-based fault diagnosis for rolling bearing
Jiaqi Li, Jinde Zheng, Haiyang Pan, et al.
Nonlinear Dynamics (2023) Vol. 111, Iss. 8, pp. 7525-7546
Closed Access | Times Cited: 5
An Intelligent Fault Diagnosis Framework for Rolling Bearings with Integrated Feature Extraction and Ordering-based Causal Discovery
Xu Ding, Junlong Wang, Hao Wu, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 10, pp. 16374-16386
Closed Access | Times Cited: 1
SPRout-DBN：A Cross Domain Bearing Fault Diagnosis Method Based on Spatial Pyramid Pooling Residual Network-DBN
D. Lin, Jiao Wei-dong, Zhilin Dong, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 12, pp. 125020-125020
Closed Access | Times Cited: 1
Time-frequency analysis-based impulse feature extraction method for quantitative evaluation of milling tool wear
MingAng Guo, Xiaotong Tu, Saqlain Abbas, et al.
Structural Health Monitoring (2023) Vol. 23, Iss. 3, pp. 1766-1778
Closed Access | Times Cited: 4
A feature extraction method for rotating machinery fault diagnosis based on a target detection index and successive variational mode decomposition
Chaofan Cao, Guangtao Zhang, Zhongliang Li, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 3, pp. 036108-036108
Closed Access | Times Cited: 2
An adaptable physics-informed fault diagnosis approach via hybrid signal processing and transferable feature learning for structural/machinery health monitoring
Milad Zarchi, Majid Shahgholi, Kong Fah Tee
Signal Image and Video Processing (2024)
Closed Access
Multi-branch convolutional attention network for multi-sensor feature fusion in intelligent fault diagnosis of rotating machinery
Ke Wu, Zirui Li, Chong Chen, et al.
Quality Engineering (2023) Vol. 36, Iss. 3, pp. 609-623
Closed Access | Times Cited: 1
Fault Diagnosis of Rolling Bearing Based on Variational Mode Decomposition and Improved Canberra Distance in Symmetrized Dot Pattern Image
Wei Wang, Jian Wang, Yongjian Sun
Journal of Artificial Intelligence Machine Learning and Data Science (2023) Vol. 1, Iss. 1, pp. 39-48
Open Access | Times Cited: 1
A Vibration Diagnosis Method for Detecting the Faults in the Planet Gear System
Jing Liu, Xinbin Li, Cheng Yan, et al.
(2022), pp. 336-342
Closed Access
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