A Mixed-Feed Identification Method for Sizer Crusher Based on Squeeze-and-Excitation Residual Network-Reference-Cited by-同舟云学术

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A Mixed-Feed Identification Method for Sizer Crusher Based on Squeeze-and-Excitation Residual Network

Published:2024-07-01 Issue:13 Volume:24 Page:21706-21718
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Bi Yankun¹^ORCID,Pan Yongtai²^ORCID,Li Guohua¹^ORCID

Affiliation:

1. School of Mechanical and Electrical Engineering, China University of Mining and Technology-Beijing, Beijing, China

2. School of Chemical and Environmental Engineering, Engineering Research Center for Mine and Municipal Solid Waste Recycling, China University of Mining and Technology-Beijing, Beijing, China

Funder

National Natural Science Foundation of China

China University of Mining and Technology-Beijing Basic Research Business Fund-Doctoral Students’ Top Innovation Talent Cultivation Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10577556/10535116.pdf?arnumber=10535116

Reference51 articles.

1. Feeding Material Identification for a Crusher Based on Deep Learning for Status Monitoring and Fault Diagnosis

2. An end-to-end harmful object identification method for sizer crusher based on time series classification and deep learning

3. Impulsive Noise Cancellation Method for Copper Ore Crusher Vibration Signals Enhancement

4. Alpha-stable distribution based methods in the analysis of the crusher vibration signals for fault detection

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