Qiuyang Zhou
Orcid: 0000-0002-1532-6551
According to our database1,
Qiuyang Zhou
authored at least 13 papers
between 2021 and 2024.
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Bibliography
2024
Multi-Node Feature Learning Network Based on Maximum Spectral Harmonics-to-Noise Ratio Deconvolution for Machine Condition Monitoring.
IEEE Trans Autom. Sci. Eng., July, 2024
A parallel ensemble optimization and transfer learning based intelligent fault diagnosis framework for bearings.
Eng. Appl. Artif. Intell., January, 2024
Dictionary Learning Method for Cyclostationarity Maximization and Its Application to Bearing Fault Feature Extraction.
IEEE Trans. Instrum. Meas., 2024
Cyclostationary harmonic product spectrum with its application for rolling bearing fault resonance frequency band adaptive location.
Expert Syst. Appl., 2024
2023
Unsupervised transfer learning for intelligent health status identification of bearing in adaptive input length selection.
Eng. Appl. Artif. Intell., November, 2023
Integrating adaptive input length selection strategy and unsupervised transfer learning for bearing fault diagnosis under noisy conditions.
Appl. Soft Comput., November, 2023
Multi-Objective Sparsity Maximum Mode De-Composition: A New Method for Rotating Machine Fault Diagnosis on High-Speed Train Axle Box.
IEEE Trans. Veh. Technol., October, 2023
A Blind Deconvolution Approach Based on Spectral Harmonics-to-Noise Ratio for Rotating Machinery Condition Monitoring.
IEEE Trans Autom. Sci. Eng., April, 2023
IEEE Trans. Instrum. Meas., 2023
A novel transfer learning network with adaptive input length selection and lightweight structure for bearing fault diagnosis.
Eng. Appl. Artif. Intell., 2023
2022
Fast Convolutional Sparse Dictionary Learning Based on LocOMP and Its Application to Bearing Fault Detection.
IEEE Trans. Instrum. Meas., 2022
2021
Blind Deconvolution Technique Based on Improved Correlated Generalized Lp/Lq Norm for Extracting Repetitive Transient Feature.
IEEE Trans. Instrum. Meas., 2021
Extracting cyclo-stationarity of repetitive transients from envelope spectrum based on prior-unknown blind deconvolution technique.
Signal Process., 2021