Name
Abstract | ||
|---|---|---|
Condition monitoring of hydraulic systems has been using automatic control in industrial system. In this paper, a sensor network based intelligent control is proposed for efficient solenoid valve identification. The detection system learns to detect the change of output pressure of multipoints that represent a more complicated task. Linear correlation analysis is introduced for feature extraction, which allows for a significant reduction in the dimension of original data without compromising the change detection performance. Implemented as an agent identifying the valve types under measurement, the support vector machine classifier achieves a significant high accuracy in identification and an increase in deployment efficiency. Experimental results prove that the system is feasible for application designs and could be implemented on technological platforms. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1155/2014/384973 | INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS |
Field | DocType | Volume |
Intelligent control,Change detection,Hydraulic machinery,Solenoid valve,Computer science,Simulation,Automatic control,Real-time computing,Feature extraction,Condition monitoring,Wireless sensor network,Distributed computing | Journal | 2014 |
ISSN | Citations | PageRank |
1550-1477 | 0 | 0.34 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yanqing Guo | 1 | 0 | 0.68 |
| Yongling Fu | 2 | 10 | 5.57 |
| Xiaoye Qi | 3 | 0 | 1.69 |
| Chun Cao | 4 | 0 | 0.34 |