曲凤成,张秀平,邱敏,曹福全.基于多元重构预测和LS-SVR的变压器故障诊断[J].电测与仪表,2014,51(15):. Qu feng-cheng,Zhang xiuping,Qiu min,Cao fu-quan.Transformer Fault Diagnosis based on Multiple Time Series Reconstruction and LS-SVR[J].Electrical Measurement & Instrumentation,2014,51(15):.
基于多元重构预测和LS-SVR的变压器故障诊断
Transformer Fault Diagnosis based on Multiple Time Series Reconstruction and LS-SVR
It can be used to find out transformer faults through the predict detection of transformer oil dissolved gas. By multivariate time series reconstruction of the state variables as LSSVR model inputs, a transformer fault prediction model was proposed. Firstly, the prediction based on multivariate reconstruction principle and LSSVR theory were given. Then, it was discussed the impact of the reconstruction parameters and LSSVR parameters for predicting errors. Genetic algorithm was adopted to ensure prediction accuracy. Finally, the method was used to verify the applicability of support vector machine prediction based on Lorenz system. Compared with other predictive approaches, the proposed combinational forecast model has higher prediction accuracy.
