Empirical mode reconstruction: Preserving intrinsic components in data augmentation for intelligent fault diagnosis of civil aviation hydraulic pumps

Author:

Meng Linghui,Zhao MinghangORCID,Cui Zhiquan,Zhang Xingming,Zhong Shisheng

Funder

National Key Research and Development Program of China

Department of Science and Technology of Shandong Province

Ministry of Science and Technology of the People's Republic of China

Natural Science Foundation of Shandong Province

Publisher

Elsevier BV

Subject

General Engineering,General Computer Science

Reference39 articles.

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2. Identification of cavitation intensity for high-speed aviation hydraulic pumps using 2D convolutional neural networks with an input of RGB-based vibration data;Chao;Meas. Sci. Technol.,2020

3. Fault diagnosis method based on integration of RSSD and wavelet transform to rolling bearing;Chen;Measurement,2019

4. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis;Huang;Proc. R. Soc. London. Ser A: Math., Phys. Eng. Sci.,1998

5. Batch normalization: accelerating deep network training by reducing internal covariate shift;Ioffe;Int. Conf. Machin. Learn.,2015

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