Power Transformer Fault Diagnosis Using Random Forest and Optimized Kernel Extreme Learning Machine
Tusongjiang Kari, Zhiyang He, Aisikaer Rouzi, Ziwei Zhang, Xiaojing Ma, Lin Du
Abstract
Power transformer is one of the most crucial devices in power grid. It is significant to determine incipient faults of power transformers fast and accurately. Input features play critical roles in fault diagnosis accuracy. In... | Find, read and cite all the research you need on Tech Science Press
Topics & Concepts
Random forestComputer scienceFeature selectionExtreme learning machineTransformerArtificial intelligenceFault (geology)Machine learningDissolved gas analysisPattern recognition (psychology)Kernel (algebra)Data miningEngineeringMathematicsArtificial neural networkTransformer oilSeismologyCombinatoricsElectrical engineeringGeologyVoltagePower Transformer Diagnostics and InsulationMachine Learning and ELMAdvanced Algorithms and Applications