Name
Title | ||
|---|---|---|
Automatic Fault Detection And Diagnosis Implementation Based On Intelligent Approaches |
Abstract | ||
|---|---|---|
Automatic fault detection and diagnosis has always been a challenge when Monitoring rotating machinery. Specifically, bearing diagnostics have seen an extensive research in the field of fault detection and diagnosis. In this paper we present two automatic diagnosis procedures -a fuzzy classifier and a neural network which deal with different implementation questions: the use of a priori knowledge, the computation cost, and the decision making process. The challenge is not only to be capable of diagnosing automatically but also to generalize the process regardless of the measured signals. Two actions are taken in order to achieve some kind of generalization of the application target: the use of normalized signals and the study of Basis Pursuit feature extraction procedure. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ETFA.2005.1612575 | ETFA 2005: 10th IEEE International Conference on Emerging Technologies and Factory Automation, Vol 1, Pts 1 and 2, Proceedings |
Keywords | Field | DocType |
a priori knowledge,machinery,neural network,basis pursuit,decision making process,artificial intelligence,feature extraction | Data mining,Normalization (statistics),Fault detection and isolation,A priori and a posteriori,Basis pursuit,Feature extraction,Artificial intelligence,Engineering,Artificial neural network,Machine learning,Decision-making,Computation | Conference |
Citations | PageRank | References |
1 | 0.43 | 3 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. Fernandez | 1 | 16 | 2.46 |
| L. Gonzalez | 2 | 1 | 0.43 |
| I. Bediaga | 3 | 1 | 0.43 |
| A. Gaston | 4 | 1 | 0.43 |
| J. Hernandez | 5 | 10 | 6.28 |