Detecting Helical Gearbox Defects from Raw Vibration Signal Using Convolutional Neural Networks
Detecting Helical Gearbox Defects from Raw Vibration Signal Using Convolutional Neural Networks
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Publisher
Basel: MDPI AG
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Language
English
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Publisher
Basel: MDPI AG
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Contents
A study on the gearbox (speed reducer) defect detection models built from the raw vibration signal measured by a triaxial accelerometer and based on convolutional neural networks (CNNs) is presented. Gear faults such as localized pitting, localized wear on helical pinion tooth flanks, and lubricant low level are under observation for three rotating...
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Full title
Detecting Helical Gearbox Defects from Raw Vibration Signal Using Convolutional Neural Networks
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TN_cdi_doaj_primary_oai_doaj_org_article_61ab95672957426fbaa8c787c0f3e541
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_61ab95672957426fbaa8c787c0f3e541
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ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s23218769
