确定电力变压器气相色谱分析结果解释方法的必要性和适用性

A. Okhlopkov, V. Bitney
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引用次数: 0

摘要

油中溶解气体的分析方法是早期发现电力充油变压器缺陷信息量最大的方法之一。现在,对变压器状态的决定是基于根据指南文件RD 153-34.0-46.302-00对气相色谱(GC)结果的解释方法。同时,在某些情况下,本文档不能提供准确的分析结果。因此,建议使用几种方法来解释气相色谱的结果,以获得精确的结论。本研究的目的是证实需要使用各种方法解释电力变压器油的气相色谱分析结果。本文综述了溶解气体分析的以下方法:Rogers比率法、IEC 60599标准法、Doernenburg比率法、Duval三角法、ETRA法以及俄罗斯联邦采用的指导文件RD 153-34.0-46.302-00方法。这些方法在俄罗斯联邦的各个电力公司实施,如PJSC“Rosseti MR”,PJSC“FGC UES”和PJSC“Mosenergo”。本文揭示了需要考虑基于RD 153-34.0-46.302-00和训练样本开发的所有可用方法和技术的总体。所进行的研究的科学新颖性和意义在于确认需要使用一套方法来解释GC的结果。本文中描述的用于解释GC和训练样本结果的方法的复杂应用的算法已经形成。所获得的结果使我们能够考虑开发软件的可能性,用于文章中描述的GC结果解释方法的复杂应用以及基于所开发的算法形成训练样本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Confirmation of necessity and applicability of using various methods of interpretation of results of gas chromatographic analysis of power transformers
The method of analysis of gases dissolved in oil is one of the most informative methods of early detection of defects in power oil-filled transformers. Now, the decision on the state of the transformers is based on the method of interpretation of the results of the gas chromatographic (GC) according to the guideline document RD 153-34.0-46.302-00. At the same time, there are situations when this document does not provide accurate analysis results. Thus, it is proposed to use several methods of interpreting the results of the GC to obtain refined conclusions. The purpose of the study is to substantiate the need to use various methods of interpretation of the results of gas chromatographic analysis of the oil of power transformers. The following methods for dissolved gas analysis have been reviewed: Rogers Ratio Method, IEC 60599 Standard Method, Doernenburg Ratio Method, Duval Triangle Method, ETRA method, as well as the guideline document RD 153-34.0-46.302-00 method adopted in the Russian Federation. These methods are implemented in various power companies of the Russian Federation, such as PJSC “Rosseti MR”, PJSC “FGC UES” and PJSC “Mosenergo”. The article reveals the need to consider the totality of all available methods and techniques based on RD 153-34.0-46.302-00 and development of training samples. The scientific novelty and significance of the conducted research lies in the confirmation of the need to use a set of methods for interpreting the results of the GC. An algorithm for the complex application of the methods described in the article for interpreting the results of the GC and training samples has been formed. The obtained results allow us to consider the possibility to develop software for the complex application of the methods of interpretation of the results of the GC described in the article and the formation of training samples based on the developed algorithm.
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