Name
Title | ||
|---|---|---|
Degradation feature extraction using multi-source monitoring data via logarithmic normal distribution based variational auto-encoder |
Abstract | ||
|---|---|---|
•A general solution is presented for degeneration features extraction of nonlinear deterioration process.•Log-Normal-Based VAE is proposed for dimensionality reduction and nonlinear deterioration feature extraction.•Experimental validation study has been carried out to demonstrate the feasibility of proposed method. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.compind.2019.04.013 | Computers in Industry |
Keywords | Field | DocType |
Fault diagnosis,Feature extraction,Multi-source data,Variational auto-encoder,Complex equipment | Normal distribution,Normalization (statistics),Autoencoder,Pattern recognition,Feature extraction,Control engineering,Condition monitoring,Artificial intelligence,Engineering,Kullback–Leibler divergence,Network model,Bayes' theorem | Journal |
Volume | ISSN | Citations |
109 | 0166-3615 | 1 |
PageRank | References | Authors |
0.36 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gen Ping | 1 | 1 | 0.36 |
| Jinglong Chen | 2 | 3 | 3.08 |
| Tongyang Pan | 3 | 3 | 4.77 |
| Jun Pan | 4 | 16 | 0.98 |