Multiple partial discharge source discrimination with multiclass support vector machines

Expert Systems with Applications

Volumn 55, Issue , 2016, Pages 417-428

  Robles, Guillermo ^a   Parrado Hernández, Emilio ^a   Ardila Rey, Jorge ^b   Martínez Tarifa, Juan Manuel ^a  

^a UNIVERSIDAD CARLOS III DE MADRID   (Spain)

^b DEPARTAMENTO DE FÍSICA   (Chile)

Author keywords

Condition monitoring; Electric maintenance; Machine learning; Partial discharges; Risk assessment; Support vector machine

Indexed keywords

ARTIFICIAL INTELLIGENCE; CONDITION MONITORING; DECISION MAKING; DECOMMISSIONING (NUCLEAR REACTORS); ELECTRIC POWER TRANSMISSION NETWORKS; EQUIPMENT; FREQUENCY DOMAIN ANALYSIS; LEARNING SYSTEMS; MAINTENANCE; PARTIAL DISCHARGES; RISK ASSESSMENT; VECTORS;

CLASSIFICATION ACCURACY; CONDITION BASED MAINTENANCE; INDUSTRIAL ENVIRONMENTS; MAINTENANCE DECISION MAKING; MULTI-CLASS SUPPORT VECTOR MACHINES; PARTIAL DISCHARGE MEASUREMENTS; PARTIAL DISCHARGE SOURCES; PHASE RESOLVED PARTIAL DISCHARGE PATTERNS;

SUPPORT VECTOR MACHINES;

EID: 84960097967     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2016.02.014     Document Type: Article

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