Name
Title | ||
|---|---|---|
The design of multiple linear regression models using a genetic algorithm to diagnose initial short-circuit faults in 3-phase induction motors. |
Abstract | ||
|---|---|---|
•Regression models are proposed to diagnose short-circuit faults in induction motors.•Genetic algorithm is used to obtain the optimal classification model.•The models can be adjusted using simulation or experimental data.•The proposed approach can be applied for real time machine monitoring. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.asoc.2017.11.015 | Applied Soft Computing |
Keywords | Field | DocType |
Induction machine,Incipient short-circuit,Non-invasive fault diagnosis,Multiple linear regression modelling,Analysis of variance,Genetic algorithms | Early detection,Induction motor,Control theory,Genetic algorithm optimization,Voltage,Short circuit,Root mean square,Artificial intelligence,Mathematics,Machine learning,Genetic algorithm,Linear regression | Journal |
Volume | Issue | ISSN |
63 | C | 1568-4946 |
Citations | PageRank | References |
1 | 0.39 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arismar M. G. Júnior | 1 | 1 | 0.39 |
| Valceres Vieira Rocha e Silva | 2 | 31 | 3.09 |
| Lane M. R. Baccarini | 3 | 23 | 2.52 |
| Lívia F. S. Mendes | 4 | 1 | 0.39 |