Name
Abstract | ||
|---|---|---|
As the accidents are frequent in the process of vacuum level measuring of vacuum interrupters and the measuring results are with bad consistency. The measuring accuracy can’t be assured by only one measuring method. More than two measuring method are used in this paper, such as the method of magnetism-control discharges and the method of shield electric-potential. Fuzzy neural networks controller is designed for each method, to realize “vertical” fuzzy judge. Then data fusion method based on fuzzy neural networks is used to realize “horizontal” fuzzy control and to gain vacuum value of highly reliability. In the end, the ineffective data is eliminated based on fusion matrix theory and whether the transducer is invalid is judged. That is utilized as the fuzzy control’s assistant method. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/FSKD.2009.173 | FSKD (3) |
Keywords | Field | DocType |
vacuum interrupter,fuzzy neural networks controller,level measuring,measuring method,fuzzy neural network,assistant method,fuzzy judge,measuring result,data fusion method,vacuum level measuring,fuzzy neural networks,measuring accuracy,fuzzy control,data fusion,sensor fusion,transducers,artificial neural networks,transducer,matrix theory,feature extraction,vacuum level | Transducer,Control theory,Pattern recognition,Computer science,Control theory,Fuzzy logic,Feature extraction,Sensor fusion,Artificial intelligence,Fuzzy control system,Artificial neural network,Vacuum level | Conference |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhizhong Zhao | 1 | 0 | 1.01 |
| Youhua Wang | 2 | 0 | 0.34 |
| Tao Liu | 3 | 0 | 0.34 |
| Haiping Xin | 4 | 0 | 0.34 |