Application of Adaptive Fuzzy Spiking Neural P Systems in Fault Diagnosis of Power Systems

摘要：

　　Adaptive fuzzy spiking neural P systems (in short,AFSN P systems) are a novel kind of computing model with the ability of parallel processing and learning.Based on our existing works,we introduce the AFSN P systems into power systems to investigate the problems of fault diagnosis and deal with the uncertainty of action messages about protective relays and breakers.The model of fault diagnosis can be easily modeled by the AFSN P system and then tested by the corresponding fuzzy reasoning mechanism.Furthermore,the learning algorithm is applied to adjust the weights in the model of fault diagnosis automatically.Two practical examples are used to demonstrate the feasibility and effectiveness of the AFSN P systems in fault diagnosis of power system.

关键词： AFSN P system Power system Fault diagnosis Fuzzy reasoning Learning algorithm

作者: Min Tu Jun Wang Hong Peng Tao Wang

作者单位: School of Electrical and Information Engineering,Xihua University, Chengdu, Sichuan, 610039, China School of Mathematics and Computer Engineering,Xihua University, Chengdu, Sichuan, 610039, China

会议类型: 国际会议

会议名称: Asian Conference on Membrane Computing (2012亚洲膜计算国际会议)(ACMC2012)

会议地点: 武汉

会议语种:英文

页码: 105-114

在线出版日期: 2012-10-15（万方平台首次上网日期，不代表论文的发表时间）