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Real-Time Intelligent Diagnosis of Co-frequency Vibration Faults in Rotating Machinery Based on Ligh...

Real-Time Intelligent Diagnosis of Co-frequency Vibration Faults in Rotating Machinery Based on Ligh...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_da3a012f617b4449a82a0228f6be8f0a

Real-Time Intelligent Diagnosis of Co-frequency Vibration Faults in Rotating Machinery Based on Lightweight-Convolutional Neural Networks

About this item

Full title

Real-Time Intelligent Diagnosis of Co-frequency Vibration Faults in Rotating Machinery Based on Lightweight-Convolutional Neural Networks

Publisher

Singapore: Springer Nature Singapore

Journal title

Chinese journal of mechanical engineering, 2024-05, Vol.37 (1), p.41-19, Article 41

Language

English

Formats

Publication information

Publisher

Singapore: Springer Nature Singapore

More information

Scope and Contents

Contents

The co-frequency vibration fault is one of the common faults in the operation of rotating equipment, and realizing the real-time diagnosis of the co-frequency vibration fault is of great significance for monitoring the health state and carrying out vibration suppression of the equipment. In engineering scenarios, co-frequency vibration faults are h...

Alternative Titles

Full title

Real-Time Intelligent Diagnosis of Co-frequency Vibration Faults in Rotating Machinery Based on Lightweight-Convolutional Neural Networks

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_da3a012f617b4449a82a0228f6be8f0a

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_da3a012f617b4449a82a0228f6be8f0a

Other Identifiers

ISSN

2192-8258,1000-9345

E-ISSN

2192-8258

DOI

10.1186/s10033-024-01021-9

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