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 Multi-Indicator Fusion-Based Approach for Fault Feature Selection and Classification of Rolling Bearings
Cheng Peng, Yuyao Ouyang, Weihua Gui, et al.
IEEE Transactions on Industrial Informatics (2022) Vol. 19, Iss. 8, pp. 8635-8643
Closed Access | Times Cited: 15

Showing 15 citing articles:

Cross-domain few-shot fault diagnosis based on meta-learning and domain adversarial graph convolutional network
Junwei Hu, Weigang Li, Yong Zhang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 136, pp. 108970-108970
Closed Access | Times Cited: 13

Rotating machinery fault diagnosis based on parameter-optimized variational mode decomposition
Haoran Du, Jixin Wang, Wenjun Qian, et al.
Digital Signal Processing (2024) Vol. 153, pp. 104590-104590
Closed Access | Times Cited: 12

Review of research on signal decomposition and fault diagnosis of rolling bearing based on vibration signal
Junning Li, Luo Wen-guang, Mengsha Bai
Measurement Science and Technology (2024) Vol. 35, Iss. 9, pp. 092001-092001
Closed Access | Times Cited: 9

Adaptive minimum noise amplitude deconvolution and its application for early fault diagnosis of rolling bearings
Xuyang Xie, Lei Zhang, Jintao Wang, et al.
Applied Acoustics (2024) Vol. 220, pp. 109962-109962
Closed Access | Times Cited: 7

An Automatic Parameter Setting Variational Mode Decomposition Method for Vibration Signals
Aina Wang, Pan Qin, Xi‐Ming Sun, et al.
IEEE Transactions on Industrial Informatics (2023) Vol. 20, Iss. 2, pp. 2053-2062
Closed Access | Times Cited: 7

Shuffle-fusion pyramid network for bearing fault diagnosis under noisy environments
Cheng Zhao, Linfeng Deng, Yuanwen Zhang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 11, pp. 116133-116133
Closed Access | Times Cited: 1

An identification method of compound faults of rolling bearings blending variational mode decomposition and vector bispectrum
Mingyue Yu, Xin Wang, Xiangdong Ge, et al.
Noise & Vibration Worldwide (2024) Vol. 55, Iss. 6-7, pp. 322-337
Closed Access

Fault diagnosis of unknown device based on dynamic model and domain generalization
Fengjin Gong, Tingqiang Wang, Xiaofang Huang, et al.
2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) (2024), pp. 338-343
Closed Access

Deep Learning based Approaches for Intelligent Industrial Machinery Health Management & Fault Diagnosis in Resource-Constrained Environments
Ali Saeed Khan, Muhammad Usman Akram, Muazzam Khan Khattak, et al.
Research Square (Research Square) (2024)
Open Access

A hybrid multi-measure and improved UMAP approach for train traction motor bearing protection state assessment
S. Liu, Yi Liu, Longjiang Shen, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 11, pp. 116119-116119
Closed Access

Dynamic Signal Adaptive Reconstruction and Multitask Knowledge Distillation for Industrial Surveillance of Hazardous Chemicals Using Gas Sensor
Hao Wang, Yong Zhao, Zhenyu Yuan, et al.
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 12, pp. 14449-14458
Closed Access

Skew Filtering for Online State Estimation and Control
Oguzhan Dogru, Ranjith Chiplunkar, Biao Huang
IEEE Transactions on Industrial Informatics (2023) Vol. 20, Iss. 2, pp. 1508-1515
Open Access

Page 1

Scroll to top