首页|基于灰色相关向量机的变压器故障预测

基于灰色相关向量机的变压器故障预测

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为有效解决特征气体数据较少情况下故障预测精度不佳的问题,将灰色预测理论与相关向量机回归预测理论相结合,构建了一种基于灰色相关向量机的变压器故障预测方法.利用训练样本对灰色相关向量机进行训练,依据特征样本数据序列建立离散灰色模型,将离散灰色模型的预测值作为输入、原始样本数据序列作为输出,从而训练获得相关向量机预测模型.使用训练好的灰色相关向量机模型对测试样本进行预测并运用故障诊断方法进行故障判断.经过实例对比分析,所提出的方法预测精度明显优于BP及SVM预测方法,具有有效性与可行性.
Grey Relevance Vector Machine-based Transformer Fault Prediction
Aiming at addressing low fault prediction accuracy in the case of inadequate characteristic gas data,this work tentatively proposed a new method to predict of transformer faults based on grey relevance vector machine by combining the grey theory and the relevance vector regression prediction.The main efforts entailed training of the grey relevance vec-tor machine,the establishment of a discrete grey model according to the data sequence of feature sample,the obtaining of the prediction model using prediction value of the discrete grey model as input and the original sample data sequence as output.The trained fault diagnosis method could then be used for fault prediction and fault determination according to rele-vant fault judgment criteria.The proposed method was indicated by comparative case analysis to have obviously superior accuracy compared to BP and SVM prediction methods,and thereby to be potentially effective and feasible.

power transformerfault predictionrelevance vector machinediscrete grey model

袁海满、钱海涛

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中国电建集团河南省电力勘测设计院有限公司,河南 郑州 450000

电力变压器 故障预测 相关向量机 离散灰色模型

2024

电工技术
重庆西南信息有限公司(原科技部西南信息中心)

电工技术

影响因子:0.177
ISSN:1002-1388
年,卷(期):2024.(21)