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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:

Use of generalized Gaussian cyclostationarity for blind deconvolution and its application to bearing fault diagnosis under non-Gaussian conditions
Dikang Peng, Xixi Zhu, Wei Teng, et al.
Mechanical Systems and Signal Processing (2023) Vol. 196, pp. 110351-110351
Closed Access | Times Cited: 20

Showing 20 citing articles:

Noise-robust adaptive feature mode decomposition method for accurate feature extraction in rotating machinery fault diagnosis
Yuyang Chen, Zhiwei Mao, Xiuqun Hou, et al.
Mechanical Systems and Signal Processing (2024) Vol. 211, pp. 111213-111213
Closed Access | Times Cited: 11
Applications of robust statistics for cyclostationarity detection in non-Gaussian signals for local damage detection in bearings
Wojciech Żuławiński, Jérôme Antoni, Radosław Zimroz, et al.
Mechanical Systems and Signal Processing (2024) Vol. 214, pp. 111367-111367
Closed Access | Times Cited: 11
On the design of Optimal Health Indicators for early fault detection and their statistical thresholds
Jérôme Antoni, Kayacan Kestel, Cédric Peeters, et al.
Mechanical Systems and Signal Processing (2024) Vol. 218, pp. 111518-111518
Closed Access | Times Cited: 9
Classifier-guided neural blind deconvolution: A physics-informed denoising module for bearing fault diagnosis under noisy conditions
Jing-Xiao Liao, Chao He, Jipu Li, et al.
Mechanical Systems and Signal Processing (2024) Vol. 222, pp. 111750-111750
Closed Access | Times Cited: 6
Feature extraction of rolling bearing based on adaptive variational multi-harmonic mode extraction
Z. Y. Wang, Chaozhong Liu
Journal of Vibroengineering (2025)
Open Access
Inference and Quantification of Cyclostationary Impulses: A novel noise-sensitive mixed Gaussian cyclostationary model for compound fault detection
Qing Zhang, Xiaofei Liu, Tianqi Li, et al.
Mechanical Systems and Signal Processing (2025) Vol. 229, pp. 112501-112501
Closed Access
Adaptive signal regime for identifying transient shifts: A novel approach toward fault diagnosis in wind turbine systems
Peng Chen, Y. Wu, Shuai Fan, et al.
Ocean Engineering (2025) Vol. 325, pp. 120798-120798
Closed Access
Adaptive maximum generalized Gaussian cyclostationarity blind deconvolution for the early fault diagnosis of high-speed train bearings under non-Gaussian noise
Defu Han, Hongyuan Qi, S. K. Wang, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102731-102731
Closed Access | Times Cited: 4
Cyclostationarity blind deconvolution via eigenvector screening and its applications to the condition monitoring of rotating machinery
Wenyu Huo, Zuhua Jiang, Zhipeng Sheng, et al.
Mechanical Systems and Signal Processing (2024) Vol. 222, pp. 111782-111782
Closed Access | Times Cited: 4
Impact time domain decomposition: An adaptive decomposition method for multi-source impact signals based on envelope energy gradient characteristics
Yuyang Chen, Jinjie Zhang, Nanyang Zhao, et al.
Mechanical Systems and Signal Processing (2024) Vol. 219, pp. 111637-111637
Closed Access | Times Cited: 2
Bearing Diagnosis Using an Anti-Noise Neural Network Based on Selectable Branch Multiscale Modules and Attention Mechanisms
Ankang Li, Dechen Yao, Jianwei Yang, et al.
IEEE Sensors Journal (2023) Vol. 24, Iss. 5, pp. 5830-5840
Closed Access | Times Cited: 5
Resilient fast nonlinear blind deconvolution with uniform initialization for the bearing fault diagnosis
Hao Ma, Baokun Han, Jinrui Wang, et al.
Structural Health Monitoring (2024)
Closed Access | Times Cited: 1
Research on rolling bearing fault diagnosis method based on Harmonic Noise Kurtosis-Time characteristic Blind Deconvolution
Jianwei Yang, Runtao Sun, Dechen Yao, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-15
Closed Access
Generalised envelope spectrum-based signal-to-noise objectives: Formulation, optimisation and application for gear fault detection under time-varying speed conditions
Stephan Schmidt, Daniël N. Wilke, Konstantinos Gryllias
Mechanical Systems and Signal Processing (2024) Vol. 224, pp. 111974-111974
Open Access
Sensitive periodic mode decomposition: an effective method for extracting periodic pulse features
Jian Cheng, Zhiheng Liu, Haiyang Pan, et al.
Nonlinear Dynamics (2024)
Closed Access
Investigation on morphological filtering via enhanced adaptive time-varying structural element for bearing fault diagnosis
Shengbo Wang, Bingyan Chen, Yao Cheng, et al.
Measurement (2024), pp. 116466-116466
Closed Access
Adaptive Maximum High-Order Cyclostationarity Blind Deconvolution Method for Rolling Bearing Fault Diagnosis
Yi Wu, Jinhai Wang, Jianwei Yang
Lecture notes in electrical engineering (2024), pp. 351-361
Closed Access
Rank-1 and Rank-Sparsity Coherence: The Intrinsic Properties for Accurate Separation of Impulse Responses of Rolling Bearing Faults
Qiqiang Fang, Zhou Meng, Hengshan Wu, et al.
(2024)
Closed Access
A novel hybrid strategy for damage detection of wind turbine yaw bearing
Xiaolong Wang, H. L. Jin, Zixiang Fu, et al.
Structural Health Monitoring (2024)
Closed Access
A New Method for Rolling Bearing Condition Evaluation Method Under Varying Speeds
Xi Gu, Yaoxiang Yu, Kexin Hou, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-10
Closed Access
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