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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:

Machinery Fault Diagnosis Based on Domain Adaptation to Bridge the Gap Between Simulation and Measured Signals
Yunxia Lou, Anil Kumar, Jiawei Xiang
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-9
Closed Access | Times Cited: 86

Showing 1-25 of 86 citing articles:

Arc fault detection using artificial intelligence: Challenges and benefits
Chunpeng Tian, Zhaoyang Xu, Lukun Wang, et al.
Mathematical Biosciences & Engineering (2023) Vol. 20, Iss. 7, pp. 12404-12432
Open Access | Times Cited: 59
Generative AI: A systematic review using topic modelling techniques
Priyanka Gupta, Bosheng Ding, Chong Guan, et al.
Data and Information Management (2024) Vol. 8, Iss. 2, pp. 100066-100066
Open Access | Times Cited: 53
Faulty rolling bearing digital twin model and its application in fault diagnosis with imbalanced samples
Yi Qin, Hongyu Liu, Yongfang Mao
Advanced Engineering Informatics (2024) Vol. 61, pp. 102513-102513
Closed Access | Times Cited: 29
Digital twin-assisted dual transfer: a novel information-model adaptation method for rolling bearing fault diagnosis
Zixian Li, Xiaoxi Ding, Zhenzhen Song, et al.
Information Fusion (2024), pp. 102271-102271
Closed Access | Times Cited: 15
A temporal-spatial multi-order weighted graph convolution network with refined feature topology graph for imbalance fault diagnosis of rotating machinery
Zhichao Jiang, Dongdong Liu, Lingli Cui
Reliability Engineering & System Safety (2025), pp. 110830-110830
Closed Access | Times Cited: 1
Intelligent fault diagnosis of worm gearbox based on adaptive CNN using amended gorilla troop optimization with quantum gate mutation strategy
Govind Vashishtha, Sumika Chauhan, Surinder Kumar, et al.
Knowledge-Based Systems (2023) Vol. 280, pp. 110984-110984
Open Access | Times Cited: 38
Intelligent fault diagnosis of bearings under small samples: A mechanism-data fusion approach
Kun Xu, Xianguang Kong, Qibin Wang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107063-107063
Closed Access | Times Cited: 29
Stable and Accurate Estimation of SOC Using eXogenous Kalman Filter for Lithium-Ion Batteries
Qizhe Lin, Xiaoqi Li, Bicheng Tu, et al.
Sensors (2023) Vol. 23, Iss. 1, pp. 467-467
Open Access | Times Cited: 27
Fault vibration model driven fault-aware domain generalization framework for bearing fault diagnosis
Bin Pang, Qiuhai Liu, Zhenli Xu, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102620-102620
Closed Access | Times Cited: 11
FedLED: Label-Free Equipment Fault Diagnosis With Vertical Federated Transfer Learning
Jie Shen, Shusen Yang, Cong Zhao, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-10
Open Access | Times Cited: 9
Knowledge Distillation-Guided Cost-Sensitive Ensemble Learning Framework for Imbalanced Fault Diagnosis
Shuaiqing Deng, Zihao Lei, Guangrui Wen, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 13, pp. 23110-23122
Closed Access | Times Cited: 7
Digital Twin-Assisted Fault Diagnosis of Rotating Machinery Without Measured Fault Data
Jingyan Xia, Ruyi Huang, Jipu Li, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-10
Closed Access | Times Cited: 7
Dynamic model-driven intelligent fault diagnosis method for rotary vector reducers
Junkang Zheng, Hui Wang, Anil Kumar, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 124, pp. 106648-106648
Closed Access | Times Cited: 20
Knowledge addition for improving the transfer learning from the laboratory to identify defects of hydraulic machinery
Anil Kumar, Adam Głowacz, Hesheng Tang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 106756-106756
Closed Access | Times Cited: 20
Latest innovations in the field of condition-based maintenance of rotatory machinery: a review
Anil Kumar, Chander Parkash, Hesheng Tang, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 2, pp. 022003-022003
Closed Access | Times Cited: 20
Incremental learning with multi-fidelity information fusion for digital twin-driven bearing fault diagnosis
Xufeng Huang, Tingli Xie, Shuyang Luo, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108212-108212
Closed Access | Times Cited: 6
Imbalanced deep transfer network for fault diagnosis of high-speed train traction motor bearings
Yilong Liu, Xinyuan Li, Xingwu Zhang, et al.
Knowledge-Based Systems (2024) Vol. 293, pp. 111682-111682
Closed Access | Times Cited: 6
Ultrasonic evaluation of wire-to-terminal joints: integrating XGBoost machine learning with finite element feature analysis
He Xu, Xiaobin Jiang, Jianzhong Guo, et al.
Nondestructive Testing And Evaluation (2024), pp. 1-18
Closed Access | Times Cited: 5
Smart systems for real-time bearing faults diagnosis by using vibro-acoustics sensor fusion with Bayesian optimised 1-D CNNs
Abdullah Al Mamun, David A. Guerra-Zubiaga, Yayu Peng
Nondestructive Testing And Evaluation (2024), pp. 1-25
Closed Access | Times Cited: 5
Research on Intelligent Prediction of Surface Roughness in Cutting 42CrMo Steel by using Particle Swarm Optimization-based Support Vector Machine
HaiYue Zhao, Yan Cao, Gorbachev Sergey, et al.
International Journal of Precision Engineering and Manufacturing (2024)
Closed Access | Times Cited: 5
Few-shot learning for estimating gear wear severity towards digital twinning
Roee Cohen, Lior Bachar, Jacob Bortman
Engineering Failure Analysis (2025), pp. 109330-109330
Open Access
Cross-domain fault diagnosis of induction motor based on an improved unsupervised generative adversarial network and fine-tuning under limited labeled data
Xin Chen, Zaigang Chen
Measurement (2025), pp. 116988-116988
Closed Access
Learning sparse convolutional neural networks through filter pruning for efficient fault diagnosis on edge devices
Gaowei Xu, Yukai Zhao, Min Liu
Nondestructive Testing And Evaluation (2025), pp. 1-23
Closed Access
Simulation-to-reality transferability framework for operating-parameter forecasting in nuclear reactors using domain adaptation
Weiqing Lin, Xi-Ren Miao, Jing Chen, et al.
Nuclear Science and Techniques (2025) Vol. 36, Iss. 5
Closed Access
Rolling bearing fault diagnosis method based on DSICNN under strong noise background
Chunli Lei, Lu Wang, Qiyue Zhang, et al.
Nondestructive Testing And Evaluation (2025), pp. 1-17
Closed Access
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