Name
Title | ||
|---|---|---|
Intelligent Condition Diagnosis Method for Rotating Machinery Based on Probability Density and Discriminant Analyses. |
Abstract | ||
|---|---|---|
This letter puts forward a method for intelligent condition diagnosis of rotating machinery using the probability density analysis and the canonical discriminant analysis (CDA) comprising the following steps. First, the noise is cancelled by statistics filter (SF), and the probability density functions (PDFs) of the vibration signals measured in each state are determined. Second, the segment value... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/LSP.2016.2575843 | IEEE Signal Processing Letters |
Keywords | Field | DocType |
Vibrations,Probability density function,Filtering theory,Frequency estimation,Machinery,Feature extraction,Band-pass filters | Centrifugal force,Band-pass filter,Pattern recognition,Discriminant,Mahalanobis distance,Feature extraction,Artificial intelligence,Linear discriminant analysis,Vibration,Probability density function,Mathematics | Journal |
Volume | Issue | ISSN |
23 | 8 | 1070-9908 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liuyang Song | 1 | 0 | 0.34 |
| Peng Chen 0002 | 2 | 0 | 0.34 |
| Huaqing Wang | 3 | 20 | 4.03 |
| Miki Kato | 4 | 10 | 3.94 |