Name
Abstract | ||
|---|---|---|
An essential step toward the development of anintelligent substation is to provide self-diagnosingcapability at the equipment level. Transformers, circuitbreakers and other substation equipment should beenabled to detect their potential failures and make lifeexpectancy prediction without human interference. Thispaper focuses on the development of an on-line equipmentdiagnostics using artificial intelligence and a nonlinearobserver to prevent catastrophic failures in substationequipment, thus providing preventive maintenance. Keyelements of the system are a nonlinear observer, systemidentifier, and fault detector that use a uniquely designedneuro-fuzzy inference engine. Experimental results fromapplication of this system to a distribution transformerare presented. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/HICSS.2003.1173904 | HICSS |
Keywords | Field | DocType |
maintenance engineering,complex data,predictive maintenance,circuit breakers,sensor fusion,preventive maintenance,artificial intelligent,life expectancy | Computer science,Distribution transformer,Knowledge management,Sensor fusion,System identifier,Circuit breaker,Inference engine,Predictive maintenance,Preventive maintenance,Maintenance engineering,Reliability engineering | Conference |
ISBN | Citations | PageRank |
0-7695-1874-5 | 0 | 0.34 |
References | Authors | |
1 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rahmat Shoureshi | 1 | 61 | 10.12 |
| Tim Norick | 2 | 0 | 0.68 |
| David Linder | 3 | 6 | 1.73 |
| John Work | 4 | 0 | 0.68 |
| Paula Kaptain | 5 | 0 | 0.34 |