计算机工程与应用2012，Vol.48Issue(23)：27-31,35,6.DOI:10.3778/j.issn.1002-8331.2012.23.006
车载牵引变压器智能故障诊断技术新研究
New research on intelligent fault diagnosis technology of on-board traction transformer
摘要
Abstract
The traction transformer faults diagnosis method is the combination of artificial intelligence algorithm and Dissolved Gas Analysis (DGA). However, due to the reasons of regeneration, sampling and chromatographic analysis, the data from DGA exist many uncertainties. In view of these, a new method combining the electric parameters and a new wavelet neural network model is proposed to diagnosis the traction transformer faults. The electric parameters work as input signal of the new network model. The hidden layer uses orthogonal Daubechies function as basis function. Learning and optimization algorithm adopts a kind of hybrid particle swarm optimization algorithm that introduces the concepts of quantum computation and immune algorithm. The test results show that the proposed intelligent faults diagnosis algorithm owns the faster diagnosis speed and higher accuracy.关键词
车载牵引变压器/短路故障/小波神经网络/混合粒子群算法Key words
on-board traction transformer/ short-circuit fault/ wavelet neural network/ hybrid particle swarm optimization分类
信息技术与安全科学引用本文复制引用
朱佼佼,陈特放,付强..车载牵引变压器智能故障诊断技术新研究[J].计算机工程与应用,2012,48(23):27-31,35,6.基金项目
国家高技术研究发展计划(863)(No.2009AA11Z217). （863）
