Fault detection method of bearing structure based on singular spectrum analysis and SOM network
Author:
Affiliation:
1. University of Jinan,School of Electrical Engineering,Jinan,China,250022
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10598401/10598402/10598773.pdf?arnumber=10598773
Reference9 articles.
1. Bridging the gap between AI and the industry — A study on bearing fault detection in PMSM-driven systems using CNN and inverter measurement
2. A novel energy demodulation method using B-spline approximation for bearing fault detection
3. Fault state identification of rolling bearings based on deep transfer convolutional autoencoder and a new health indicator
4. Application of improved bubble entropy and machine learning in the adaptive diagnosis of rotating machinery faults
5. Detection and identification of windmill bearing faults using a one-class support vector machine (SVM)
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