A Genetic Programming Based Fuzzy Model for Fault Diagnosis of Power Transformers

Created by W.Langdon from gp-bibliography.bib Revision:1.8178

@InProceedings{Zhang:2010:ICINIS,

• author = "Zheng Zhang and Kangling Fang and Weihua Huang",
• title = "A Genetic Programming Based Fuzzy Model for Fault Diagnosis of Power Transformers",
• booktitle = "3rd International Conference on Intelligent Networks and Intelligent Systems (ICINIS 2010)",
• year = "2010",
• month = "1-3 " # nov,
• pages = "455--458",
• abstract = "In this paper, a fuzzy model based on genetic programming (GPFM) is proposed to diagnose the fault types of insulation of power transformers. The proposed GPFM algorithm constructs the fuzzy relationship between input and output fuzzy variables by genetic programming algorithms. The parameters of memberships of fuzzy subsets and the fuzzy relationship of system are represented by the GP candidates that have the form of tree-like combinations of fuzzy subsets of input variables. Then the best fuzzy function is evolved by genetic operations and evolution. Based on the proposed GPFM algorithms, an insulation fault diagnosis system for power systems is designed to distinguish the insulation fault types of power transformers. Compared with the conditional fuzzy IEC code method, the GPFM algorithm can automatically generate fuzzy relationship between fault symptom with fault types and shows better performances.",
• keywords = "genetic algorithms, genetic programming, fuzzy IEC code method, fuzzy subsets, genetic programming based fuzzy model, insulation fault diagnosis system, power transformers, tree-like combinations, fuzzy set theory, power transformers",
• DOI = "doi:10.1109/ICINIS.2010.154",
• notes = "Coll. of Inf. Sci. & Eng., Wuhan Univ. of Sci. & Technol., Wuhan, China. Also known as \cite{5693583}",

}

Genetic Programming entries for Zheng Zhang Kangling Fang Weihua Huang

Citations