Autocorrelation aided random forest classifier-based bearing fault detection framework

SS Roy, S Dey, S Chatterjee - IEEE Sensors Journal, 2020 - ieeexplore.ieee.org
Rolling bearing defects in induction motors are usually diagnosed using vibration signal
analysis. For accurate detection of rolling bearing defects, appropriate feature extraction …
被引用次数：127 相关文章

[引用][C] Autocorrelation Aided Random Forest Classifier-Based Bearing Fault Detection Framework

SS Roy, S Dey, S Chatterjee - IEEE Sensors Journal, 2020 - ui.adsabs.harvard.edu
Autocorrelation Aided Random Forest Classifier-Based Bearing Fault Detection Framework -
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[引用][C] Autocorrelation Aided Random Forest Classifier-Based Bearing Fault Detection Framework

SS Roy, S Dey, S Chatterjee - IEEE Sensors Journal, 2020 - cir.nii.ac.jp
Autocorrelation Aided Random Forest Classifier-Based Bearing Fault Detection Framework |
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