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Bearing fault detection is a challenging task, especially at the incipient stage.
The efficiency of bearing fault diagnosis is thus further improved.
This phenomenon is an early bearing fault feature.
The envelope order spectrum is used for bearing fault identification.
Planetary gearboxes exhibit unique challenges in bearing fault detection.
Experimental results using different bearing fault types and severities under different loads show that the proposed method is well-suited and effective for bearing fault classification.
We report a non-resonance based approach to bearing fault detection.
The extraction of repetitive impacts from vibration signals plays an essential role in bearing fault detection.
The results demonstrate its effectiveness and robustness for motor bearing fault detection and classification.
The application of the proposed method to bearing fault detection is explored.
However, the methods are only applicable for offline bearing fault detection.
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