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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:

Corrosion leakage risk diagnosis of oil and gas pipelines based on semi-supervised domain generalization model
Xingyuan Miao, Hong Zhao, Boxuan Gao, et al.
Reliability Engineering & System Safety (2023) Vol. 238, pp. 109486-109486
Closed Access | Times Cited: 20

Showing 20 citing articles:

Multi-scale style generative and adversarial contrastive networks for single domain generalization fault diagnosis
Jun Wang, He Ren, Changqing Shen, et al.
Reliability Engineering & System Safety (2023) Vol. 243, pp. 109879-109879
Closed Access | Times Cited: 41
A domain feature decoupling network for rotating machinery fault diagnosis under unseen operating conditions
Tianyu Gao, Jingli Yang, Wenmin Wang, et al.
Reliability Engineering & System Safety (2024) Vol. 252, pp. 110449-110449
Closed Access | Times Cited: 15
Multi-modal cascade detection of pipeline defects based on deep transfer metric learning
Boxuan Gao, Hong Zhao, Xingyuan Miao
Engineering Failure Analysis (2024) Vol. 160, pp. 108216-108216
Closed Access | Times Cited: 8
Three-layer and robust planning models to evaluate the strategies of defense layer, attack layer, and operation layer for optimal protection in natural gas pipeline network
Jun Zhou, Jiaxing Zhu, Guangchuan Liang, et al.
Reliability Engineering & System Safety (2024) Vol. 249, pp. 110196-110196
Closed Access | Times Cited: 5
Natural gas pipeline weak leakage detection based on negative pressure wave decomposition and feature enhancement
Ye Lin, Chengyou Wang, Xiao Zhou, et al.
Reliability Engineering & System Safety (2025), pp. 110857-110857
Closed Access
Application of machine learning to leakage detection of fluid pipelines in recent years: A review and prospect
Jianwu Chen, Xiao Wu, Zhibo Jiang, et al.
Measurement (2025), pp. 116857-116857
Closed Access
Study on the transient structure and acoustic emission characteristics of gas pipeline leakage holes at leakage instant
Fei Tang, Yueping Qin, Peng Wang, et al.
Physics of Fluids (2025) Vol. 37, Iss. 3
Closed Access
Intelligent diagnosis of gas pipeline condition through multivariate analysis of acoustic emission signal-based imaging
Md Junayed Hasan, Khandaker Noman, Wasib Ul Navid, et al.
Nondestructive Testing And Evaluation (2025), pp. 1-20
Closed Access
Residual strength prediction of corroded pipelines based on physics-informed machine learning and domain generalization
Tingting Wu, Xingyuan Miao, Fulin Song
npj Materials Degradation (2025) Vol. 9, Iss. 1
Open Access
Prediction on Failure Pressure of Pipeline Containing Corrosion Defects Based on ISSA-BPNN Model
Zhuang Qi, Dong Liu, Zhuo Chen
Energy Engineering (2024) Vol. 121, Iss. 3, pp. 821-834
Open Access | Times Cited: 3
Leakage diagnosis of natural gas pipeline based on multi-source heterogeneous information fusion
Xingyuan Miao, Hong Zhao
International Journal of Pressure Vessels and Piping (2024) Vol. 209, pp. 105202-105202
Closed Access | Times Cited: 3
Chemical fault diagnosis network based on single domain generalization
Yu Guo, Jundong Zhang
Process Safety and Environmental Protection (2024) Vol. 188, pp. 1133-1144
Closed Access | Times Cited: 2
An Improved Convolutional Neural Network for Pipe Leakage Identification Based on Acoustic Emission
Weidong Xu, Jiwei Huang, Lianghui Sun, et al.
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 10, pp. 1720-1720
Open Access | Times Cited: 2
Simulation data-driven attention fusion network with multi-similarity metric: A single-domain generalization diagnostic method for tie rod bolt loosening of a rod-fastening rotor system
Chen Zhou, Jun He, Xin Xiong, et al.
Measurement (2024) Vol. 240, pp. 115565-115565
Closed Access | Times Cited: 1
A study of neural network-based evaluation methods for pipelines with multiple corrosive regions
Zhiwei Zhang, LI Song-ling, Huajie Wang, et al.
Reliability Engineering & System Safety (2024), pp. 110507-110507
Closed Access | Times Cited: 1
Multi-Parameter Maximum Corrosion Depth Prediction Model for Buried Pipelines Based on GSCV-XGBoost
Niannian Wang, Liuyang Song, Hongyuan Fang, et al.
IEEE Access (2023) Vol. 11, pp. 116452-116471
Open Access | Times Cited: 4
NDAMA: A Novel Deep Autoencoder and Multivariate Analysis Approach for IoT-Based Methane Gas Leakage Detection
Khongorzul Dashdondov, Mi-Hye Kim, Kyuri Jo
IEEE Access (2023) Vol. 11, pp. 140740-140751
Open Access | Times Cited: 3
A Review of Deformations Prediction for Oil and Gas Pipelines Using Machine and Deep Learning
Bruno Macedo, Tales Humberto de Aquino Boratto, Camila Martins Saporetti, et al.
Studies in systems, decision and control (2024), pp. 289-317
Closed Access
A Zero-Shot Learning Approach for Blockage Detection and Identification Based on the Stacking Ensemble Model
Chaoqun Li, Zao Feng, Mingkai Jiang, et al.
Sensors (2024) Vol. 24, Iss. 17, pp. 5596-5596
Open Access
Graph embedded patch-sense autoencoder with prior knowledge for multi-component system anomaly detection
Shen Liu, Jinglong Chen, Zijun Liu, et al.
Reliability Engineering & System Safety (2024), pp. 110784-110784
Closed Access
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