Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Condition monitoring and performance forecasting of wind turbines based on denoising autoencoder and novel convolutional neural networks
Xiongjie Jia, Yang Han, Yanjun Li, et al.
Energy Reports (2021) Vol. 7, pp. 6354-6365
Open Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Advancements of wind energy conversion systems for low-wind urban environments: A review
Tan Jian Ding, Clifford Choe Wei Chang, Mohammad Arif Sobhan Bhuiyan, et al.
Energy Reports (2022) Vol. 8, pp. 3406-3414
Open Access | Times Cited: 58
Towards efficient and effective renewable energy prediction via deep learning
Zulfiqar Ahmad Khan, Tanveer Hussain, Ijaz Ul Haq, et al.
Energy Reports (2022) Vol. 8, pp. 10230-10243
Open Access | Times Cited: 50
Solar Power Prediction Using Dual Stream CNN-LSTM Architecture
Hamad Alharkan, Shabana Habib, Muhammad Islam
Sensors (2023) Vol. 23, Iss. 2, pp. 945-945
Open Access | Times Cited: 28
Fault detection in wind turbine generators using a meta-learning-based convolutional neural network
Likui Qiao, Yuxian Zhang, Qisen Wang
Mechanical Systems and Signal Processing (2023) Vol. 200, pp. 110528-110528
Closed Access | Times Cited: 28
A state-of-the-art review on wind power converter fault diagnosis
Jinping Liang, Ke Zhang, Ahmed Al‐Durra, et al.
Energy Reports (2022) Vol. 8, pp. 5341-5369
Open Access | Times Cited: 36
Remaining useful life prediction of rolling bearings based on TCN-MSA
Guang‐Jun Jiang, Zheng-Wei Duan, Qi Zhao, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 2, pp. 025125-025125
Closed Access | Times Cited: 18
A review of SCADA-based condition monitoring for wind turbines via artificial neural networks
Li Sheng, Chunyu Li, Ming Gao, et al.
Neurocomputing (2025), pp. 129830-129830
Closed Access
Condition Monitoring and Fault Detection of Wind Turbine Driveline With the Implementation of Deep Residual Long Short-Term Memory Network
Yuwei He, Jiayang Liu, Shijing Wu, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 12, pp. 13360-13376
Closed Access | Times Cited: 12
Review of several key processes in wind power forecasting: Mathematical formulations, scientific problems, and logical relations
Mao Yang, Y. Huang, Chuanyu Xu, et al.
Applied Energy (2024) Vol. 377, pp. 124631-124631
Closed Access | Times Cited: 4
Feasibility of soft computing techniques for estimating the long-term mean monthly wind speed
Shahab S. Band, Sina Ardabili, Amir Mosavi, et al.
Energy Reports (2021) Vol. 8, pp. 638-648
Open Access | Times Cited: 31
Exploring Quantum Machine Learning and Feature Reduction Techniques for Wind Turbine Pitch Fault Detection
Camila Correa-Jullian, Sergio Cofre-Martel, Gabriel San Martín, et al.
Energies (2022) Vol. 15, Iss. 8, pp. 2792-2792
Open Access | Times Cited: 18
Bearing fault diagnosis of wind turbines based on dynamic multi-adversarial adaptive network
Miao Tian, Xiaoming Su, Changzheng Chen, et al.
Journal of Mechanical Science and Technology (2023) Vol. 37, Iss. 4, pp. 1637-1651
Closed Access | Times Cited: 11
A Lightweight CNN for Wind Turbine Blade Defect Detection Based on Spectrograms
Yuefan Zhu, Xiaoying Liu
Machines (2023) Vol. 11, Iss. 1, pp. 99-99
Open Access | Times Cited: 10
Condition monitoring of wind turbine based on a novel spatio-temporal feature aggregation network integrated with adaptive threshold interval
Lixiao Cao, Jie Zhang, Qian Zheng, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102676-102676
Closed Access | Times Cited: 3
Artificial Intelligence and Numerical Weather Prediction Models: A Technical Survey
Muhammad Waqas, Usa Wannasingha Humphries, Bunthid Chueasa, et al.
Natural Hazards Research (2024)
Open Access | Times Cited: 3
A differential privacy-preserving federated learning scheme with predictive maintenance of wind turbines based on deep learning for feature compression and anomaly detection with state assessment
Huan Chen, Hsin-Yao Hsu, Jia‐You Hsieh, et al.
Journal of Mechanical Science and Technology (2024) Vol. 38, Iss. 7, pp. 3413-3429
Closed Access | Times Cited: 2
Multi-head self-attention bidirectional gated recurrent unit for end-to-end remaining useful life prediction of mechanical equipment
Changchang Che, Huawei Wang, Xiaomei Ni, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 11, pp. 115115-115115
Closed Access | Times Cited: 13
A case study of wind turbine rotor over-speed fault diagnosis using combination of SCADA data, vibration analyses and field inspection
Majid Morshedizadeh, Marianne Rodgers, Andre Doucette, et al.
Engineering Failure Analysis (2023) Vol. 146, pp. 107056-107056
Closed Access | Times Cited: 7
Condition monitoring in wind turbines
M. Lydia, G. Edwin Prem Kumar
Elsevier eBooks (2023), pp. 229-247
Closed Access | Times Cited: 6
A Review on Wind Power Forecasting Regarding Impacts on the System Operation, Technical Challenges, and Applications
Tolga Depçi, Mustafa İncı, Murat Mustafa Savrun, et al.
Energy Technology (2022) Vol. 10, Iss. 8
Closed Access | Times Cited: 5
A Fault Detection Method Based on an Oil Temperature Forecasting Model Using an Improved Deep Deterministic Policy Gradient Algorithm in the Helicopter Gearbox
Lei Wei, Zhe Cheng, Junsheng Cheng, et al.
Entropy (2022) Vol. 24, Iss. 10, pp. 1394-1394
Open Access | Times Cited: 5
Transfer learning applications for autoencoder-based anomaly detection in wind turbines
Cyriana M. A. Roelofs, Christian Gück, Stefan Faulstich
Energy and AI (2024) Vol. 17, pp. 100373-100373
Open Access
Bi-LSTM Autoencoder SCADA based Unsupervised Anomaly Detection in Real Wind Farm Data
Bassel Chokr, Nizar Chatti, Abdérafi Charki, et al.
(2024), pp. 174-183
Closed Access
Remaining Useful Life Prediction of Wind Turbine Gearbox Bearings with Limited Samples Based on Prior Knowledge and PI-LSTM
Zheng Wang, Peng Gao, Xuening Chu
Sustainability (2022) Vol. 14, Iss. 19, pp. 12094-12094
Open Access | Times Cited: 3
Wind Turbine Spindle Operating State Recognition and Early Warning Driven by SCADA Data
Yuhan Liu, Yuqiao Zheng, Zhuang Ma, et al.
Energy Engineering (2023) Vol. 120, Iss. 5, pp. 1223-1237
Open Access | Times Cited: 1
Page 1 - Next Page

Scroll to top