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:

A novel approach of multisensory fusion to collaborative fault diagnosis in maintenance
Haidong Shao, Jing Lin, Liangwei Zhang, et al.
Information Fusion (2021) Vol. 74, pp. 65-76
Closed Access | Times Cited: 229

Showing 1-25 of 229 citing articles:

A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges
Weihua Li, Ruyi Huang, Jipu Li, et al.
Mechanical Systems and Signal Processing (2021) Vol. 167, pp. 108487-108487
Open Access | Times Cited: 540
Dual-Threshold Attention-Guided GAN and Limited Infrared Thermal Images for Rotating Machinery Fault Diagnosis Under Speed Fluctuation
Haidong Shao, Wei Li, Baoping Cai, et al.
IEEE Transactions on Industrial Informatics (2023) Vol. 19, Iss. 9, pp. 9933-9942
Closed Access | Times Cited: 181
Rolling Element Fault Diagnosis Based on VMD and Sensitivity MCKD
Hongjiang Cui, Ying Guan, Huayue Chen
IEEE Access (2021) Vol. 9, pp. 120297-120308
Open Access | Times Cited: 137
FGDAE: A new machinery anomaly detection method towards complex operating conditions
Shen Yan, Haidong Shao, Zhishan Min, et al.
Reliability Engineering & System Safety (2023) Vol. 236, pp. 109319-109319
Open Access | Times Cited: 118
CFCNN: A novel convolutional fusion framework for collaborative fault identification of rotating machinery
Yadong Xu, Ke Feng, Xiaoan Yan, et al.
Information Fusion (2023) Vol. 95, pp. 1-16
Closed Access | Times Cited: 104
A review on deep learning in planetary gearbox health state recognition: methods, applications, and dataset publication
Dongdong Liu, Lingli Cui, Weidong Cheng
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 012002-012002
Closed Access | Times Cited: 92
Fractional-Order Controller for Course-Keeping of Underactuated Surface Vessels Based on Frequency Domain Specification and Improved Particle Swarm Optimization Algorithm
Guangyu Li, Yanxin Li, Huayue Chen, et al.
Applied Sciences (2022) Vol. 12, Iss. 6, pp. 3139-3139
Open Access | Times Cited: 81
Highly imbalanced fault diagnosis of mechanical systems based on wavelet packet distortion and convolutional neural networks
Minghang Zhao, Xuyun Fu, Yongjian Zhang, et al.
Advanced Engineering Informatics (2022) Vol. 51, pp. 101535-101535
Closed Access | Times Cited: 71
A multi-source domain information fusion network for rotating machinery fault diagnosis under variable operating conditions
Tianyu Gao, Jingli Yang, Qing Tang
Information Fusion (2024) Vol. 106, pp. 102278-102278
Closed Access | Times Cited: 61
Multi-sensor data fusion-enabled semi-supervised optimal temperature-guided PCL framework for machinery fault diagnosis
Xingxing Jiang, Xuegang Li, Qian Wang, et al.
Information Fusion (2023) Vol. 101, pp. 102005-102005
Closed Access | Times Cited: 60
Non-contact diagnosis for gearbox based on the fusion of multi-sensor heterogeneous data
Dingyi Sun, Yongbo Li, Sixiang Jia, et al.
Information Fusion (2023) Vol. 94, pp. 112-125
Closed Access | Times Cited: 45
Multi-Sensor data fusion in intelligent fault diagnosis of rotating machines: A comprehensive review
Fasikaw Kibrete, Dereje Engida Woldemichael, Hailu Shimels Gebremedhen
Measurement (2024) Vol. 232, pp. 114658-114658
Closed Access | Times Cited: 40
Multi-sensor fusion fault diagnosis method of wind turbine bearing based on adaptive convergent viewable neural networks
Xinming Li, Yanxue Wang, Jiachi Yao, et al.
Reliability Engineering & System Safety (2024) Vol. 245, pp. 109980-109980
Closed Access | Times Cited: 38
Digital twin-assisted dual transfer: a novel information-model adaptation method for rolling bearing fault diagnosis
Zixian Li, Xiaoxi Ding, Zhenzhen Song, et al.
Information Fusion (2024), pp. 102271-102271
Closed Access | Times Cited: 26
Extended attention signal transformer with adaptive class imbalance loss for Long-tailed intelligent fault diagnosis of rotating machinery
Shuyuan Chang, Liyong Wang, Mingkuan Shi, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102436-102436
Closed Access | Times Cited: 21
Multi-source fault data fusion diagnosis method based on hyper-feature space graph collaborative embedding
Xiaoxin Dong, Hua Ding, Dawei Gao, et al.
Advanced Engineering Informatics (2025) Vol. 64, pp. 103092-103092
Closed Access | Times Cited: 3
Fault prognosis of Li-ion batteries in electric vehicles: Recent progress, challenges and prospects
Heng Li, Muaaz Bin Kaleem, Kailong Liu, et al.
Journal of Energy Storage (2025) Vol. 116, pp. 116002-116002
Closed Access | Times Cited: 3
Incorporating image representation and texture feature for sensor-based gymnastics activity recognition
Chao Lian, Yuliang Zhao, Tianang Sun, et al.
Knowledge-Based Systems (2025), pp. 113076-113076
Closed Access | Times Cited: 2
Fault diagnosis of wind turbine bearing using a multi-scale convolutional neural network with bidirectional long short term memory and weighted majority voting for multi-sensors
Zifei Xu, Xuan Mei, Xinyu Wang, et al.
Renewable Energy (2021) Vol. 182, pp. 615-626
Open Access | Times Cited: 91
An integrated deep multiscale feature fusion network for aeroengine remaining useful life prediction with multisensor data
Xingqiu Li, Hongkai Jiang, Yuan Liu, et al.
Knowledge-Based Systems (2021) Vol. 235, pp. 107652-107652
Closed Access | Times Cited: 76
Fast nonlinear blind deconvolution for rotating machinery fault diagnosis
Zongzhen Zhang, Jinrui Wang, Shunming Li, et al.
Mechanical Systems and Signal Processing (2022) Vol. 187, pp. 109918-109918
Closed Access | Times Cited: 66
A nearly end-to-end deep learning approach to fault diagnosis of wind turbine gearboxes under nonstationary conditions
Liangwei Zhang, Qi Fan, Jing Lin, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 119, pp. 105735-105735
Closed Access | Times Cited: 66
Semi-supervised multi-scale attention-aware graph convolution network for intelligent fault diagnosis of machine under extremely-limited labeled samples
Zongliang Xie, Jinglong Chen, Yong Feng, et al.
Journal of Manufacturing Systems (2022) Vol. 64, pp. 561-577
Closed Access | Times Cited: 65
A novel self-training semi-supervised deep learning approach for machinery fault diagnosis
Jianyu Long, Yibin Chen, Zhe Yang, et al.
International Journal of Production Research (2022) Vol. 61, Iss. 23, pp. 8238-8251
Closed Access | Times Cited: 62
Cross-domain fault diagnosis of bearing using improved semi-supervised meta-learning towards interference of out-of-distribution samples
Jian Lin, Haidong Shao, Zhishan Min, et al.
Knowledge-Based Systems (2022) Vol. 252, pp. 109493-109493
Closed Access | Times Cited: 56
Page 1 - Next Page

Scroll to top