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Deep residual learning with demodulated time-frequency features for fault diagnosis of planetary gearbox under nonstationary running conditions

PaperCitations, authors & open-access status

Deep residual learning with demodulated time-frequency features for fault diagnosis of planetary gearbox under nonstationary running conditions is a paper indexed in ScholarIQ from OpenAlex. ScholarIQ records 120 citations, 2019 year and closed oa status.

120
Citations
2019
Year
closed
OA Status

Related on ScholarIQ

Sai Ma
Author
Qinkai Han
Author
Machine Fault Diagnosis Techniques
Topic
Machine Fault Diagnosis Techniques
Topic
Gear and Bearing Dynamics Analysis
Topic
Fault Detection and Control Systems
Topic
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