Intelligent Fault Diagnosis of Rolling BearingBased on Deep Transfer Learning Using Time-Frequency Representation

Kavianpour, Mohammadreza; Ghorvei, Mohammadreza; Ramezani, Amin; Beheshti, Mohammad Taghi Hamidi

doi:10.1109/icspis54653.2021.9729385

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Intelligent Fault Diagnosis of Rolling BearingBased on Deep Transfer Learning Using Time-Frequency Representation

Cited by 3 publications

References 26 publications

A CNN-BiLSTM model with attention mechanism for earthquake prediction

A CNN-BiLSTM model with attention mechanism for earthquake prediction

Deep Multi-scale Dilated Convolution Neural Network with Attention Mechanism: A Novel Method for Earthquake Magnitude Classification

Rotary Machinery Fault Diagnosis Based on Split Attention Mechanism and Graph Convolutional Domain Adaptive Adversarial Network

Contact Info

Product

Resources

About