Fault Diagnosis Method of Rotating Machinery Based on Multi-Sensor Information Decision-Level Fusion
Author:
Affiliation:
1. Harbin Institute of Technology,Department of Automatic Test and Control,Harbin,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10482420/10482375/10482632.pdf?arnumber=10482632
Reference16 articles.
1. Parallel network using intrinsic component filtering for rotating machinery fault diagnosis
2. A novel deep stacking least squares support vector machine for rolling bearing fault diagnosis
3. An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings
4. Motor fault diagnosis using attention mechanism and improved adaboost driven by multi-sensor information
5. A convolutional neural network based on a capsule network with strong generalization for bearing fault diagnosis
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