Application of Mutual Information Maximization Convolutional Neural Network in Bearing Feature Extraction-Reference-Cited by-同舟云学术

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Application of Mutual Information Maximization Convolutional Neural Network in Bearing Feature Extraction

Published:2023-12-15 Issue:24 Volume:23 Page:30584-30592
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Wang Zhenya¹^ORCID,Zhou Chuan²,Wu Xing³^ORCID,Liu Tao¹,Kang Yi¹

Affiliation:

1. School of Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, China

2. Xi’an Precision Machinery Research Institute, Xi’an, China

3. Yunnan Vocational College of Mechanical and Electrical Technology, Kunming, China

Funder

National Natural Science Foundation of China

Key Scientific Research Projects of Yunnan Province

Yunnan Provincial School Education Cooperation Key Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10360293/10261440.pdf?arnumber=10261440

Reference26 articles.

1. Definition of Signal-to-Noise Ratio of Health Indicators and Its Analytic Optimization for Machine Performance Degradation Assessment

2. Interpretable online updated weights: Optimized square envelope spectrum for machine condition monitoring and fault diagnosis

3. Fault Diagnosis of a Rolling Bearing Using Wavelet Packet Denoising and Random Forests

4. Autoencoder-based representation learning and its application in intelligent fault diagnosis: A review

5. 1D convolutional neural networks and applications: A survey

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1. A TinyDL Model for Gesture-Based Air Handwriting Arabic Numbers and Simple Arabic Letters Recognition;IEEE Access;2024

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