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Analysis of influencing factors of Dissolved Gas in oil

机译:油中溶解气体的影响因素分析

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As an important means of insulation testing, Dissolved Gas Analysis (DGA) in oil reflect the insulation condition of transformer. However, a lot of factors influence the dissolved gas of transformer. Some of them should be taken into consideration during the analysis, especially when it comes to the typical gas concentration. In this paper, an evaluate method of influencing factors is proposed. With this method, the effect degree of influence is quantified and the typical gas concentration could be modified. Firstly, collect and process the DGA data, removing invalid data and filling missing data. Then, classify DGA data according to each influence factor. With the different classification, each cluster center can be figure out by K-means. Calculate the average Euclidean distance of cluster centers as the influence evaluating indicator. Each kind of classification corresponding to a Euclidean distance value, regard the Euclidean distance value as the influence level. The further distance means the greater influence. Finally, classify the data according to the influencing factor and calculate the typical value with the statistic method. As an example, DGA data from two grid has been collected and tested. It comes to a conclusion that voltage grade, operation years, oil type have much stronger influence than the installation location. According to the conclusion, the classification of DGA has been done and typical gas concentration which corresponds to voltage grade, operation years, oil type has been calculated. The field test shows that, with the modified typical gas concentration, the defect was identified correctly, which means the great value of this method.
机译:作为绝缘测试的重要手段,油中溶解气体分析(DGA)反映了变压器的绝缘状况。但是,有很多因素影响变压器的溶解气体。在分析过程中应考虑其中一些因素,特别是在典型气体浓度方面。本文提出了一种影响因素的评价方法。通过这种方法,可以确定影响的程度,并且可以修改典型的气体浓度。首先,收集并处理DGA数据,删除无效数据并填充丢失的数据。然后,根据每个影响因素对DGA数据进行分类。通过不同的分类,每个聚类中心都可以通过K-means来确定。计算聚类中心的平均欧几里德距离作为影响评估指标。对应于欧几里得距离值的每种分类,都以欧几里得距离值作为影响等级。距离越远意味着影响越大。最后,根据影响因素对数据进行分类,并采用统计方法计算出典型值。例如,已经收集并测试了来自两个网格的DGA数据。得出的结论是,电压等级,运行年限,机油类型比安装位置具有更大的影响。根据结论,对DGA进行了分类,计算出了与电压等级,运行年限,机油类型相对应的典型气体浓度。现场测试表明,采用改进后的典型气体浓度,可以正确地识别出缺陷,这意味着该方法的巨大价值。

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