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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:

Semi-supervised learning for industrial fault detection and diagnosis: A systemic review
José Miguel Ramírez‐Sanz, Jose-Alberto Maestro-Prieto, Álvar Arnaiz‐González, et al.
ISA Transactions (2023) Vol. 143, pp. 255-270
Open Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

Novel Domain-Adaptive Wasserstein Generative Adversarial Networks for Early Bearing Fault Diagnosis under Various Conditions
Z. K. Hei, Weifang Sun, Haiyang Yang, et al.
Reliability Engineering & System Safety (2025), pp. 110847-110847
Closed Access | Times Cited: 2
Evaluating and comparing machine learning approaches for effective decision making in renewable microgrid systems
Ismail Elabbassi, Mohamed Khala, Naima Elyanboiy, et al.
Results in Engineering (2024) Vol. 21, pp. 101888-101888
Open Access | Times Cited: 13
Data-Driven Process Monitoring and Fault Diagnosis: A Comprehensive Survey
Afrânio Melo, Maurício Melo Câmara, José Carlos Pinto
Processes (2024) Vol. 12, Iss. 2, pp. 251-251
Open Access | Times Cited: 11
A holistic semi-supervised method for imbalanced fault diagnosis of rotational machinery with out-of-distribution samples
Zhangjun Wu, Renli Xu, Yuansheng Luo, et al.
Reliability Engineering & System Safety (2024) Vol. 250, pp. 110297-110297
Closed Access | Times Cited: 9
Optimized data driven fault detection and diagnosis in chemical processes
Nahid Raeisi Ardali, Reza Zarghami, Rahmat Sotudeh‐Gharebagh
Computers & Chemical Engineering (2024) Vol. 186, pp. 108712-108712
Closed Access | Times Cited: 8
Ensemble methods and semi-supervised learning for information fusion: A review and future research directions
José Luis Garrido‐Labrador, Ana Serrano-Mamolar, Jesús Maudes, et al.
Information Fusion (2024) Vol. 107, pp. 102310-102310
Open Access | Times Cited: 6
Hypergraph construction using Multi-Sensor for helicopter Tail-Drive system fault diagnosis
Aijun Yin, Zhaoyi Sun, Junlin Zhou
Measurement (2024) Vol. 231, pp. 114586-114586
Closed Access | Times Cited: 5
A novel dynamic nonlinear non-Gaussian approach for fault detection and diagnosis
Yihan Ma, Fei Ye, Dazi Li, et al.
Neurocomputing (2025), pp. 129403-129403
Closed Access
Robust contrastive learning based on evidential uncertainty for open-set semi-supervised industrial fault diagnosis
Shuaijie Chen, Chuang Peng, Lei Chen, et al.
ISA Transactions (2025)
Closed Access
Data-driven machinery fault diagnosis: A comprehensive review
Dhiraj Neupane, Mohamed Reda Bouadjenek, Richard Dazeley, et al.
Neurocomputing (2025), pp. 129588-129588
Open Access
Artificial Intelligence for Quality Defects in the Automotive Industry: A Systemic Review
Oswaldo Morales Matamoros, José Guillermo Takeo Nava, Jesús Jaime Moreno Escobar, et al.
Sensors (2025) Vol. 25, Iss. 5, pp. 1288-1288
Open Access
Pattern Detection in Abnormal District Heating Data
Gideon Mbiydzenyuy, Håkan Sundell
Lecture notes in computer science (2025), pp. 224-239
Closed Access
Advancements in AI-Based Anomaly Detection for Smart Manufacturing
Md. Rashedul Islam, Fahmid Al Farid
Springer series in advanced manufacturing (2025), pp. 37-68
Closed Access
Industrial Applications of AI in Aircraft Manufacturing: A PRISMA Systematic Literature Review
Pierrick BOUGAULT, Raphael Haddad, Liang Ma
Research Square (Research Square) (2025)
Closed Access
Dual graph driven-consistent representation learning method for semi-supervised fault diagnosis of rotating machinery
Zhichao Jiang, Dongdong Liu, Huaqing Wang, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103274-103274
Closed Access
Semi-supervised diagnosis of wind-turbine gearbox misalignment and imbalance faults
P. Maestro, José Miguel Ramírez‐Sanz, Andrés Bustillo, et al.
Applied Intelligence (2024) Vol. 54, Iss. 6, pp. 4525-4544
Open Access | Times Cited: 4
Semi-supervised few-shot fault diagnosis driven by multi-head dynamic graph attention network under speed fluctuations
Li Jiang, Shuaiyu Wang, Tianao Zhang, et al.
Digital Signal Processing (2024) Vol. 151, pp. 104528-104528
Closed Access | Times Cited: 3
Cross-domain Intelligent Diagnostics for Rotating Machinery Using Domain Adaptive and Adversarial Networks
Kui Hu, Yiwei Cheng, Jun Wu, et al.
Journal of Industrial Information Integration (2024) Vol. 42, pp. 100722-100722
Closed Access | Times Cited: 2
IPORF: A combined improved parrot optimizer algorithm and random forest for fault diagnosis in AUV
Kangzheng Huang, Wei Bo Li, Fang Hualiang, et al.
Ocean Engineering (2024) Vol. 313, pp. 119665-119665
Closed Access | Times Cited: 2
Fault detection research on novel transfer learning-based method for cross-condition, cross-system and cross-operation in public building HVAC sensors
Boyan Zhang, Yacine Rezgui, Zhiwen Luo, et al.
Energy (2024) Vol. 313, pp. 133704-133704
Closed Access | Times Cited: 2
Fault detection for Li-ion batteries of electric vehicles with segmented regression method
Muaaz Bin Kaleem, Yun Zhou, Jiang Fu, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
A Semi-Supervised Adaptive Matrix Machine Approach for Fault Diagnosis in Railway Switch Machine
Wenqing Li, Zhongwei Xu, Meng Mei, et al.
Sensors (2024) Vol. 24, Iss. 13, pp. 4402-4402
Open Access | Times Cited: 1
Semi-supervised adaptive anti-noise meta-learning for few-shot industrial gearbox fault diagnosis
Junwei Hu, Chao Xie
Measurement Science and Technology (2024) Vol. 35, Iss. 11, pp. 116104-116104
Closed Access | Times Cited: 1
A feature extension and reconstruction method with incremental learning capabilities under limited samples for intelligent diagnosis
Kui Hu, Zhihao Bi, Qingbo He, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102796-102796
Closed Access | Times Cited: 1
A simulation data-driven semi-supervised framework based on MK-KNN graph and ESSGAT for bearing fault diagnosis
Yuyan Li, Tiantian Wang, Jingsong Xie, et al.
ISA Transactions (2024)
Closed Access | Times Cited: 1
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