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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 analysis of process fault diagnosis methods from safety perspectives
Rajeevan Arunthavanathan, Faisal Khan, Salim Ahmed, et al.
Computers & Chemical Engineering (2020) Vol. 145, pp. 107197-107197
Closed Access | Times Cited: 125

Showing 26-50 of 125 citing articles:

Alarm rationalization and dynamic risk analyses for rare abnormal events
Vikram Sudarshan, Warren D. Seider, Amish J. Patel, et al.
Computers & Chemical Engineering (2024) Vol. 184, pp. 108633-108633
Closed Access | Times Cited: 6
Graph-guided masked autoencoder for process anomaly detection
Mingwei Jia, Danya Xu, Tao Yang, et al.
Process Safety and Environmental Protection (2024) Vol. 186, pp. 1345-1357
Closed Access | Times Cited: 6
Semi-supervised process monitoring based on self-training PCA model
Junhua Zheng, Lingjian Ye, Zhiqiang Ge
Process Safety and Environmental Protection (2024) Vol. 187, pp. 1311-1321
Closed Access | Times Cited: 6
Unsupervised transfer learning for fault diagnosis across similar chemical processes
Ruoshi Qin, Feiya Lv, Huawei Ye, et al.
Process Safety and Environmental Protection (2024) Vol. 190, pp. 1011-1027
Closed Access | Times Cited: 6
Non-Intrusive Load Monitoring in industrial settings: A systematic review
Giulia Tanoni, Emanuele Principi, Stefano Squartini
Renewable and Sustainable Energy Reviews (2024) Vol. 202, pp. 114703-114703
Open Access | Times Cited: 6
Cross-domain fault diagnosis for multimode green ammonia synthesis process based on DA-CycleGAN
Yu Hua, Wenjing Chen, Heping Jin, et al.
Process Safety and Environmental Protection (2024) Vol. 191, pp. 52-64
Closed Access | Times Cited: 6
Causality-embedded reconstruction network for high-resolution fault identification in chemical process
Feiya Lv, Xiaotian Bi, Zhihai Xu, et al.
Process Safety and Environmental Protection (2024) Vol. 186, pp. 1011-1033
Closed Access | Times Cited: 5
Information Enhanced Slow Feature Analysis Integrated with Prior Fault Data for Sensitive Monitoring of Chemical Processes
Xiaogang Deng, Wenjie Yang, Yuping Cao, et al.
Process Safety and Environmental Protection (2024)
Closed Access | Times Cited: 5
Research on robustness of five typical data-driven fault diagnosis models for nuclear power plants
Jiangkuan Li, Meng Lin
Annals of Nuclear Energy (2021) Vol. 165, pp. 108639-108639
Closed Access | Times Cited: 29
Incipient fault detection of nonlinear chemical processes based on probability-related randomized slow feature analysis
Xiaogang Deng, Xuepeng Zhang, Xiaoyue Liu, et al.
Process Safety and Environmental Protection (2022) Vol. 169, pp. 797-807
Closed Access | Times Cited: 20
Detection and diagnosis of process fault using unsupervised learning methods and unlabeled data
Abdalhamid Rahoma, Syed Imtiaz, Salim Ahmed, et al.
International Journal of Advances in Engineering Sciences and Applied Mathematics (2023) Vol. 15, Iss. 1, pp. 24-36
Closed Access | Times Cited: 13
Structured fault information-aided canonical variate analysis model for dynamic process monitoring
Siwei Lou, Ping Wu, Chunjie Yang, et al.
Journal of Process Control (2023) Vol. 124, pp. 54-69
Closed Access | Times Cited: 12
Robust and sparse canonical correlation analysis for fault detection and diagnosis using training data with outliers
Lijia Luo, Weida Wang, Shiyi Bao, et al.
Expert Systems with Applications (2023) Vol. 236, pp. 121434-121434
Closed Access | Times Cited: 12
A Novel Fault Detection Scheme Based on Mutual k-Nearest Neighbor Method: Application on the Industrial Processes with Outliers
Jian Wang, Zhe Zhou, Zuxin Li, et al.
Processes (2022) Vol. 10, Iss. 3, pp. 497-497
Open Access | Times Cited: 17
Fault Diagnosis of the Dynamic Chemical Process Based on the Optimized CNN-LSTM Network
Honghua Chen, Jian Cen, Zhuohong Yang, et al.
ACS Omega (2022) Vol. 7, Iss. 38, pp. 34389-34400
Open Access | Times Cited: 17
Dual attention bidirectional generative adversarial network for dynamic uncertainty process monitoring and diagnosis
Xujia Tang, Weipeng Lu, Xuefeng Yan
Process Safety and Environmental Protection (2023) Vol. 171, pp. 214-224
Closed Access | Times Cited: 11
Industrial process fault diagnosis based on domain adaptive broad echo network
Miao Mou, Xiaoqiang Zhao
Journal of the Taiwan Institute of Chemical Engineers (2024) Vol. 159, pp. 105453-105453
Closed Access | Times Cited: 4
Can Focusing on One Deep Learning Architecture Improve Fault Diagnosis Performance?
João Gonçalves Neto, Karla Figueiredo, João B. P. Soares, et al.
Journal of Chemical Information and Modeling (2025)
Open Access
A unified model integrating Granger causality-based causal discovery and fault diagnosis in chemical processes
Feiya Lv, Borui Yang, Shujian Yu, et al.
Computers & Chemical Engineering (2025), pp. 109028-109028
Closed Access
Is the real-time data of process safety reliable? An anomaly detection method based on the Graph Neural Network
Jianrong Zhang, Wei Zhang, Wenbin Liao, et al.
Process Safety and Environmental Protection (2025), pp. 107066-107066
Closed Access
Intelligent fault diagnosis based on similarity analysis using generative model and multi-sensor fusion in industrial processes
Amir Shirshahi, Behzad Moshiri, Mahdi Aliyari-Shoorehdeli
Process Safety and Environmental Protection (2025), pp. 107097-107097
Closed Access
One-dimensional decoupled convolutional autoencoder with sparse self-attention mechanism for process monitoring
Yuguo Yang, Hongbo Shi, Bing Song, et al.
Process Safety and Environmental Protection (2025), pp. 107156-107156
Closed Access
Fuzzy Echo State Network-Based Fault Diagnosis of Remote-Controlled Robotic Arms
Shurong Peng, Zhenjiang Guo, Xiaoxu Liu, et al.
Applied Sciences (2025) Vol. 15, Iss. 11, pp. 5829-5829
Open Access
A knowledge transfer-based intelligent decision support method for fault management
Chang Tian, Pengcheng Gao, Feng Yin, et al.
Journal of Process Control (2025) Vol. 151, pp. 103452-103452
Closed Access
Big data and machine learning: A roadmap towards smart plants
Bogdan Dorneanu, Sushen Zhang, Hang Ruan, et al.
Frontiers of Engineering Management (2022) Vol. 9, Iss. 4, pp. 623-639
Open Access | Times Cited: 15

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