CAJ | 학술논문

通过对变压器油中溶解气体进行预测，可以及早发现变压器故障。提出将多变量时间序列重建的状态变量作为 LS -SVR 模型输入，建立变压器故障的预测模型。首先，给出基于多元重构的预测原理和 LS -SVR 理论。然后，讨论重构参数和 LS -SVR 参数对于预测误差的影响，通过合理选择参数确保预测的精度。最后，将该方法用于变压器故障诊断实例以验证多元重构和支持向量机预测的适用性，通过与多种预测方法进行比较，基于 LS -SVR 原理的变压器故障组合预测模型的预测精度明显优于单一预测模型和其它的组合预测模型。
통과대변압기유중용해기체진행예측，가이급조발현변압기고장。제출장다변량시간서렬중건적상태변량작위 LS -SVR 모형수입，건립변압기고장적예측모형。수선，급출기우다원중구적예측원리화 LS -SVR 이론。연후，토론중구삼수화 LS -SVR 삼수대우예측오차적영향，통과합리선택삼수학보예측적정도。최후，장해방법용우변압기고장진단실례이험증다원중구화지지향량궤예측적괄용성，통과여다충예측방법진행비교，기우 LS -SVR 원리적변압기고장조합예측모형적예측정도명현우우단일예측모형화기타적조합예측모형。
Transformer faults can be found through prediction of the dissolved gas in the transformer oil .With the state variables in the multivariate time series reconstruction as the inputs of the LS -SVR model, a transformer fault predic-tion model was proposed.Firstly, the prediction principle based on multiple reconstruction and LS -SVR theory were introduced.Then, the effects of the reconstruction parameters and LS -SVR parameters on predicting errors were dis -cussed.The parameters were reasonably chosen to ensure prediction accuracy .Finally, the proposed method was used in the actual transformer fault diagnosis in order to verify the applicability of multiple reconstruction and support vector machine prediction.Compared with other predicting approaches , the proposed transformer fault combination predicting model based on the LS -SVR theory has higher prediction accuracy than any single predicting model or any other combination predicting model.