用灰色多变量模型预测变压器油中溶解的气体浓度

XIAO Yancai; ZHU Hengjun; CHEN Xiuhai

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用灰色多变量模型预测变压器油中溶解的气体浓度

更新时间：2025-08-13

- 用灰色多变量模型预测变压器油中溶解的气体浓度
- Automation of Electric Power Systems Vol. 30, Issue 13, (2006)
- 作者机构：
  
  1. 北京交通大学机电学院,北京市,100044
  2. 北京电力公司,北京市,100031
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2006
- 稿件说明：
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XIAO Yancai, ZHU Hengjun, CHEN Xiuhai. [J]. Automation of electric power systems, 2006, 30(13).
DOI：

XIAO Yancai, ZHU Hengjun, CHEN Xiuhai. [J]. Automation of electric power systems, 2006, 30(13). DOI：

摘要

目前变压器油中气体浓度预测普遍采用GM(1

1)模型及其改进形式，针对其在建模时只单独考虑某种气体发展变化的不足，介绍了灰色多变量预测模型MGM(1

n)，它可以综合考虑从同一信号中提取的多个诊断指标，因而预测更科学、有效。对变压器油中溶解的7种特征气体即氢气、甲烷、乙烷、乙烯、乙炔、一氧化碳和二氧化碳进行了灰色关联分析，建立了相应的MGM(1

7)模型，预测实例分析证明，与传统GM(1

1)模型及其改进形式相比，用灰色多变量模型预测的效果更好。

Abstract

Currently available prediction models for dissolved gases in transformer oil are GM(1

1) and its improved forms

which have the drawback of considering only one gas separately. To make up for this disadvantage

the multivariable grey model MGM(1

n) is introduced to allow for the change in several indices described simultaneously. Thus

the prediction with the multivariable grey model has proved more scientific and effective. The relationship between seven dissolved characteristic gases

viz. hydrogen (H2)

methane (CH4)

ethane (C2H6)

ethylene (C2H4)

acetylene (C2H2)

carbon monoxide (CO)

and carbon dioxide (CO2)

based on the grey relational analysis theory is discussed. The MGM(1

7) model is then developed. Finally

the effectiveness and superiority of the proposed method has been verified with the result of an actual case.

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