Name
Title | ||
|---|---|---|
Feature Denoising and Nearest-Farthest Distance Preserving Projection for Machine Fault Diagnosis. |
Abstract | ||
|---|---|---|
It is a big challenge to identify the most effective features for enhancement of fault classification accuracy in rotating machines due to nonstationary and nonlinear vibration characteristics of the machines under varying operating conditions. To find discriminative features, a novel dimension reduction algorithm, referred to as the nearest and farthest distance preserving projection (NFDPP), is ... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TII.2015.2475219 | IEEE Transactions on Industrial Informatics |
Keywords | Field | DocType |
Noise reduction,Feature extraction,Vibrations,Noise,Fault diagnosis,Classification algorithms,Time-domain analysis | k-nearest neighbors algorithm,Time domain,Feature vector,Dimensionality reduction,Pattern recognition,Computer science,Feature (computer vision),Feature extraction,Bearing (mechanical),Artificial intelligence,Statistical classification | Journal |
Volume | Issue | ISSN |
12 | 1 | 1551-3203 |
Citations | PageRank | References |
16 | 0.74 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li Weihua | 1 | 35 | 11.36 |
| Shaohui Zhang | 2 | 61 | 9.77 |
| Subhash Rakheja | 3 | 220 | 23.05 |