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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:

A comprehensive study on Structural Health Monitoring (SHM) of wind turbine blades by instrumenting tower using machine learning methods
Meghdad Khazaee, Pierre Dérian, Anthony Mouraud
Renewable Energy (2022) Vol. 199, pp. 1568-1579
Open Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

Floating Offshore Wind Turbines: Current Status and Future Prospects
Mohammad Barooni, Turaj Ashuri, Deniz Velioglu Sogut, et al.
Energies (2022) Vol. 16, Iss. 1, pp. 2-2
Open Access | Times Cited: 68
Deep Learning for Structural Health Monitoring: Data, Algorithms, Applications, Challenges, and Trends
Jing Jia, Ying Li
Sensors (2023) Vol. 23, Iss. 21, pp. 8824-8824
Open Access | Times Cited: 32
Acoustic-Signal-Based Damage Detection of Wind Turbine Blades—A Review
Shaohu Ding, Chenchen Yang, Sen Zhang
Sensors (2023) Vol. 23, Iss. 11, pp. 4987-4987
Open Access | Times Cited: 31
A Review of thermoplastic composites on wind turbine blades
Xiangrong Cheng, Bing Du, He Jia, et al.
Composites Part B Engineering (2025), pp. 112411-112411
Closed Access | Times Cited: 1
A Novel CNN-LSTM Hybrid Model for Prediction of Electro-Mechanical Impedance Signal Based Bond Strength Monitoring
Lukesh Parida, Sumedha Moharana, Victor Ferreira, et al.
Sensors (2022) Vol. 22, Iss. 24, pp. 9920-9920
Open Access | Times Cited: 30
A single-sensor method for structural damage localization in wind turbine blades: Laboratory assessment on a blade segment
Zhimin Zhao, Nian-Zhong Chen
Mechanical Systems and Signal Processing (2024) Vol. 214, pp. 111370-111370
Closed Access | Times Cited: 7
Noise effects analysis on subspace-based damage detection with neural networks
Marco Martino Rosso, Angelo Aloisio, Jonathan Melchiorre, et al.
Structures (2023) Vol. 54, pp. 23-37
Closed Access | Times Cited: 12
Probabilistic estimation of directional wave spectrum using onboard measurement data
Myong-Jin Park, Yooil Kim
Journal of Marine Science and Technology (2024) Vol. 29, Iss. 1, pp. 200-220
Closed Access | Times Cited: 4
A Novel Small-Scale Wind-Turbine Blade Failure Detection According to Monitored-Data
Ali Aranizadeh, Hesam Khorrami Shad, Behrooz Vahidi, et al.
Results in Engineering (2024), pp. 103809-103809
Open Access | Times Cited: 4
Introduction to Wind Farm Micro-siting
Prateek Mittal, Kishalay Mitra
(2025), pp. 1-24
Closed Access
Reliable Remote Technique for SHM of Offshore Windmills Supporting Structures
Mohamed I. S. Elmasry
Structural Engineering International (2025), pp. 1-10
Closed Access
Unsupervised transfer learning for monitoring CFRP responses using discrete strains
Yan Huai, Songhe Meng, Bo Gao, et al.
International Journal of Mechanical Sciences (2025), pp. 110142-110142
Closed Access
Artificial Intelligence and Data Analytics for Structural Health Monitoring: A Review of Recent Developments
Shrikant M. Harle, Amol P. Bhagat, Rahul S. Ingole, et al.
Archives of Computational Methods in Engineering (2025)
Closed Access
Domain-separated capsule network for damage detection in aluminum plates under varying vibration conditions
Qi Jiang, Xin Huang, Wenzhong Qu, et al.
Ultrasonics (2025), pp. 107688-107688
Closed Access
Structural health monitoring of jacket-type support structures in offshore wind turbines: A comprehensive dataset for bolt loosening detection through vibrational analysis
Rhandall Valdez-Yepez, Christian Tutivén, Yolanda Vidal
Data in Brief (2024) Vol. 53, pp. 110222-110222
Open Access | Times Cited: 3
In Situ Structural Health Monitoring of Full-Scale Wind Turbine Blades in Operation Based on Stereo Digital Image Correlation
Weiwu Feng, Yang Da, DU Wen-xue, et al.
Sustainability (2023) Vol. 15, Iss. 18, pp. 13783-13783
Open Access | Times Cited: 7
Structural health monitoring on operating offshore wind turbine blade via a single accelerometer: Feasibility study by simulation and experiment
Dahai Zhang, Tao Zhao, Bohan Wang, et al.
Measurement (2024) Vol. 244, pp. 116432-116432
Closed Access | Times Cited: 2
Mechanical, Electrical, and Tensile Self-Sensing Properties of Ultra-High-Performance Concrete Enhanced with Sugarcane Bagasse Ash
Jinkang Lian, Yulin Wang, Tengfei Fu, et al.
Materials (2023) Vol. 17, Iss. 1, pp. 82-82
Open Access | Times Cited: 6
Method using singular value decomposition and whale optimization algorithm to quantitatively detect multiple damages in turbine blades
Hu Jiang, Yongying Jiang, Jiawei Xiang
Structural Health Monitoring (2023) Vol. 23, Iss. 2, pp. 1025-1036
Closed Access | Times Cited: 4
Towards an Intelligent Tomorrow
Kassim Kalinaki, Silviu Florin Acaru, Julius Kugonza, et al.
Advances in computational intelligence and robotics book series (2024), pp. 66-89
Closed Access | Times Cited: 1
Fault diagnosis for wind turbine generators based on Model-Agnostic Meta-Learning: A few-shot learning method
Likui Qiao, Yuxian Zhang, Qisen Wang, et al.
Expert Systems with Applications (2024), pp. 126171-126171
Closed Access | Times Cited: 1
The Use of Coherence Functions of Acoustic Emission Signals as a Method for Diagnosing Wind Turbine Blades
A. Bejger, Jan Drzewieniecki, Przemysław Bartoszko, et al.
Energies (2023) Vol. 16, Iss. 22, pp. 7474-7474
Open Access | Times Cited: 3
Analysis of FBG Based Sensing for Infrastructure Structural Health Monitoring Applications
Uģis Seņkāns, Jānis Braunfelds, Sandis Spolītis, et al.
2022 Photonics & Electromagnetics Research Symposium (PIERS) (2023), pp. 744-753
Closed Access | Times Cited: 2
WHEN IS AN SHM PROBLEM A MULTI-TASK- LEARNING PROBLEM?
Sarah Bee, Lawrence A. Bull, Nikolaos Dervilis, et al.
Proceedings of the 13th International Workshop on Structural Health Monitoring (2023)
Open Access | Times Cited: 1
Operational Sensor Adjustment for Structural Health Monitoring Systems in Wind Turbines using Machine Learning
Johannes Rupfle, Bernhard Wondra, Markus Nowack
Research Square (Research Square) (2024)
Open Access
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