Name
Abstract | ||
|---|---|---|
The paper proposed a monitoring system for the circuit breakers in the substation based on the Back Propagation Neural Networks(BPNN). The novel temperature and humidity sensor was used in the system to get temperature and humidity value in the breakers. The carbon resistor displacement sensor was employed to get the displacement data of the contact in the closing or breaking procedure. All the data was transferred into the BPNN to obtain the remainder service life of the breakers set and give an alarm for the malfunction. In the experiments, the parameters were measured and the results showed that the system in this paper was efficient. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/MVHI.2010.194 | MVHI |
Keywords | Field | DocType |
humidity value,propagation neural networks,novel temperature,monitoring system,humidity sensor,displacement data,carbon resistor displacement sensor,circuit breaker,remainder service life,circuit breakers,neural network,intelligent systems,voltage,neural networks,backpropagation,neural nets,service life,humidity | Computer vision,Service life,Monitoring system,ALARM,Computer science,Remainder,Circuit breaker,Resistor,Artificial intelligence,Artificial neural network,Backpropagation,Electrical engineering | Conference |
Citations | PageRank | References |
1 | 0.41 | 1 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yimin Hou | 1 | 5 | 2.91 |
| Tao Liu | 2 | 67 | 22.11 |
| Xiangmin Lun | 3 | 3 | 1.84 |
| Jianjun Lan | 4 | 1 | 0.75 |
| Yang Cui | 5 | 1 | 2.10 |