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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.

How many citations does Deep residual learning with demodulated time-frequency features for fault diagnosis of planetary gearbox under nonstationary running conditions have?

ScholarIQcitation count

Deep residual learning with demodulated time-frequency features for fault diagnosis of planetary gearbox under nonstationary running conditions has 120 citations in the OpenAlex counts ScholarIQ stores.

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

ScholarIQyear

Deep residual learning with demodulated time-frequency features for fault diagnosis of planetary gearbox under nonstationary running conditions has 2019 year in the ScholarIQ index.

What is the open-access status of Deep residual learning with demodulated time-frequency features for fault diagnosis of planetary gearbox under nonstationary running conditions?

ScholarIQoa status

Deep residual learning with demodulated time-frequency features for fault diagnosis of planetary gearbox under nonstationary running conditions has closed oa status in the ScholarIQ index.

What is the DOI of Deep residual learning with demodulated time-frequency features for fault diagnosis of planetary gearbox under nonstationary running conditions?

ScholarIQdoi

The DOI for Deep residual learning with demodulated time-frequency features for fault diagnosis of planetary gearbox under nonstationary running conditions is on the source record.

What is the OpenAlex record for Deep residual learning with demodulated time-frequency features for fault diagnosis of planetary gearbox under nonstationary running conditions?

ScholarIQopenalex

The OpenAlex for Deep residual learning with demodulated time-frequency features for fault diagnosis of planetary gearbox under nonstationary running conditions is on the source record.

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